data_source
stringclasses 1
value | prompt
stringlengths 949
8.38k
| ability
stringclasses 1
value | reward_model
dict | extra_info
dict |
|---|---|---|---|---|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
86, experimental_model_of_disease
118, organophosphorus_compound
7, therapeutic_or_preventive_procedure
src, edge_attr, dst
86, result_of, 7
118, affects, 86
118, causes, 86
7, affects, 86
7, associated_with, 86
7, complicates, 86
7, prevents, 86
7, treats, 86
Question: For what reason are experimental_model_of_disease, organophosphorus_compound, and therapeutic_or_preventive_procedure associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"experimental_model_of_disease",
"organophosphorus_compound",
"therapeutic_or_preventive_procedure"
],
"valid_edges": [
[
"experimental_model_of_disease",
"result_of",
"therapeutic_or_preventive_procedure"
],
[
"organophosphorus_compound",
"affects",
"experimental_model_of_disease"
],
[
"organophosphorus_compound",
"causes",
"experimental_model_of_disease"
],
[
"therapeutic_or_preventive_procedure",
"affects",
"experimental_model_of_disease"
],
[
"therapeutic_or_preventive_procedure",
"associated_with",
"experimental_model_of_disease"
],
[
"therapeutic_or_preventive_procedure",
"complicates",
"experimental_model_of_disease"
],
[
"therapeutic_or_preventive_procedure",
"prevents",
"experimental_model_of_disease"
],
[
"therapeutic_or_preventive_procedure",
"treats",
"experimental_model_of_disease"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
26, amino_acid_sequence
3, carbohydrate_sequence
86, experimental_model_of_disease
42, geographic_area
70, idea_or_concept
32, molecular_sequence
134, nucleotide_sequence
67, research_device
79, spatial_concept
src, edge_attr, dst
26, isa, 70
26, isa, 32
26, isa, 79
3, isa, 70
3, isa, 32
3, isa, 79
42, associated_with, 86
42, isa, 70
42, isa, 79
32, isa, 70
32, isa, 79
134, isa, 70
134, isa, 32
134, isa, 79
67, causes, 86
79, isa, 70
Question: For what reason are carbohydrate_sequence, experimental_model_of_disease, and research_device associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"carbohydrate_sequence",
"experimental_model_of_disease",
"research_device"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"geographic_area",
"associated_with",
"experimental_model_of_disease"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"research_device",
"causes",
"experimental_model_of_disease"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
8, chemical_viewed_functionally
62, disease_or_syndrome
89, finding
src, edge_attr, dst
8, affects, 62
8, causes, 62
89, associated_with, 62
89, evaluation_of, 62
89, manifestation_of, 62
Question: In what context are chemical_viewed_functionally, disease_or_syndrome, and finding connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"chemical_viewed_functionally",
"disease_or_syndrome",
"finding"
],
"valid_edges": [
[
"chemical_viewed_functionally",
"affects",
"disease_or_syndrome"
],
[
"chemical_viewed_functionally",
"causes",
"disease_or_syndrome"
],
[
"finding",
"associated_with",
"disease_or_syndrome"
],
[
"finding",
"evaluation_of",
"disease_or_syndrome"
],
[
"finding",
"manifestation_of",
"disease_or_syndrome"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
123, diagnostic_procedure
50, event
128, health_care_related_organization
src, edge_attr, dst
123, isa, 50
128, carries_out, 123
128, location_of, 123
Question: For what reason are diagnostic_procedure, event, and health_care_related_organization associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"diagnostic_procedure",
"event",
"health_care_related_organization"
],
"valid_edges": [
[
"diagnostic_procedure",
"isa",
"event"
],
[
"health_care_related_organization",
"carries_out",
"diagnostic_procedure"
],
[
"health_care_related_organization",
"location_of",
"diagnostic_procedure"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
57, amino_acid_peptide_or_protein
61, clinical_drug
68, drug_delivery_device
75, food
99, hazardous_or_poisonous_substance
113, manufactured_object
59, medical_device
84, substance
src, edge_attr, dst
57, ingredient_of, 61
57, interacts_with, 99
57, isa, 84
61, isa, 113
68, contains, 61
68, isa, 113
68, isa, 59
75, ingredient_of, 61
75, isa, 84
99, ingredient_of, 61
99, isa, 84
59, isa, 113
84, ingredient_of, 61
Question: How are amino_acid_peptide_or_protein, drug_delivery_device, and hazardous_or_poisonous_substance related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_peptide_or_protein",
"drug_delivery_device",
"hazardous_or_poisonous_substance"
],
"valid_edges": [
[
"amino_acid_peptide_or_protein",
"ingredient_of",
"clinical_drug"
],
[
"amino_acid_peptide_or_protein",
"interacts_with",
"hazardous_or_poisonous_substance"
],
[
"amino_acid_peptide_or_protein",
"isa",
"substance"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"hazardous_or_poisonous_substance",
"ingredient_of",
"clinical_drug"
],
[
"hazardous_or_poisonous_substance",
"isa",
"substance"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"substance",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
80, mental_or_behavioral_dysfunction
119, organism
67, research_device
src, edge_attr, dst
80, affects, 119
80, process_of, 119
67, causes, 80
Question: For what reason are mental_or_behavioral_dysfunction, organism, and research_device associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"mental_or_behavioral_dysfunction",
"organism",
"research_device"
],
"valid_edges": [
[
"mental_or_behavioral_dysfunction",
"affects",
"organism"
],
[
"mental_or_behavioral_dysfunction",
"process_of",
"organism"
],
[
"research_device",
"causes",
"mental_or_behavioral_dysfunction"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
44, body_part_organ_or_organ_component
132, body_system
107, educational_activity
33, eicosanoid
70, idea_or_concept
111, qualitative_concept
src, edge_attr, dst
44, conceptual_part_of, 132
44, produces, 33
132, isa, 70
111, evaluation_of, 107
111, isa, 70
Question: How are body_part_organ_or_organ_component, educational_activity, and eicosanoid related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_part_organ_or_organ_component",
"educational_activity",
"eicosanoid"
],
"valid_edges": [
[
"body_part_organ_or_organ_component",
"conceptual_part_of",
"body_system"
],
[
"body_part_organ_or_organ_component",
"produces",
"eicosanoid"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
26, amino_acid_sequence
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
50, event
124, family_group
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
99, hazardous_or_poisonous_substance
53, health_care_activity
70, idea_or_concept
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
111, qualitative_concept
66, regulation_or_law
67, research_device
122, social_behavior
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
26, isa, 17
26, isa, 70
64, associated_with, 28
64, associated_with, 124
64, isa, 69
64, isa, 50
48, isa, 17
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
107, isa, 69
107, isa, 50
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
42, isa, 17
42, isa, 70
91, isa, 69
91, isa, 50
10, isa, 17
10, property_of, 28
10, property_of, 124
99, ingredient_of, 61
53, isa, 69
53, isa, 50
70, conceptual_part_of, 64
70, isa, 17
55, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
66, affects, 28
66, affects, 124
66, isa, 17
122, associated_with, 28
122, associated_with, 124
122, isa, 69
122, isa, 50
Question: For what reason are amino_acid_sequence, daily_or_recreational_activity, and hazardous_or_poisonous_substance associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_sequence",
"daily_or_recreational_activity",
"hazardous_or_poisonous_substance"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"amino_acid_sequence",
"isa",
"conceptual_entity"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"hazardous_or_poisonous_substance",
"ingredient_of",
"clinical_drug"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
36, machine_activity
80, mental_or_behavioral_dysfunction
7, therapeutic_or_preventive_procedure
src, edge_attr, dst
36, method_of, 7
80, result_of, 7
7, affects, 80
7, associated_with, 80
7, complicates, 80
7, prevents, 80
7, treats, 80
Question: For what reason are machine_activity, mental_or_behavioral_dysfunction, and therapeutic_or_preventive_procedure associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"machine_activity",
"mental_or_behavioral_dysfunction",
"therapeutic_or_preventive_procedure"
],
"valid_edges": [
[
"machine_activity",
"method_of",
"therapeutic_or_preventive_procedure"
],
[
"mental_or_behavioral_dysfunction",
"result_of",
"therapeutic_or_preventive_procedure"
],
[
"therapeutic_or_preventive_procedure",
"affects",
"mental_or_behavioral_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"associated_with",
"mental_or_behavioral_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"complicates",
"mental_or_behavioral_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"prevents",
"mental_or_behavioral_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"treats",
"mental_or_behavioral_dysfunction"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
9, entity
56, mental_process
108, temporal_concept
src, edge_attr, dst
56, occurs_in, 108
108, isa, 9
108, result_of, 56
Question: In what context are entity, mental_process, and temporal_concept connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"entity",
"mental_process",
"temporal_concept"
],
"valid_edges": [
[
"mental_process",
"occurs_in",
"temporal_concept"
],
[
"temporal_concept",
"isa",
"entity"
],
[
"temporal_concept",
"result_of",
"mental_process"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
102, biologically_active_substance
85, laboratory_procedure
1, population_group
src, edge_attr, dst
85, analyzes, 102
85, assesses_effect_of, 102
85, measures, 102
1, performs, 85
Question: For what reason are biologically_active_substance, laboratory_procedure, and population_group associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biologically_active_substance",
"laboratory_procedure",
"population_group"
],
"valid_edges": [
[
"laboratory_procedure",
"analyzes",
"biologically_active_substance"
],
[
"laboratory_procedure",
"assesses_effect_of",
"biologically_active_substance"
],
[
"laboratory_procedure",
"measures",
"biologically_active_substance"
],
[
"population_group",
"performs",
"laboratory_procedure"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
48, classification
61, clinical_drug
17, conceptual_entity
107, educational_activity
47, enzyme
50, event
124, family_group
91, governmental_or_regulatory_activity
53, health_care_activity
128, health_care_related_organization
55, intellectual_product
27, occupational_activity
31, organization
118, organophosphorus_compound
41, professional_society
111, qualitative_concept
66, regulation_or_law
40, self_help_or_relief_organization
src, edge_attr, dst
28, isa, 17
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 27
28, produces, 48
28, produces, 61
28, produces, 55
28, produces, 66
28, uses, 48
28, uses, 61
28, uses, 55
28, uses, 66
48, isa, 17
48, isa, 55
107, isa, 69
107, isa, 50
107, isa, 27
47, ingredient_of, 61
124, isa, 17
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 27
124, produces, 48
124, produces, 61
124, produces, 55
124, produces, 66
124, uses, 48
124, uses, 61
124, uses, 55
124, uses, 66
91, isa, 69
91, isa, 50
91, isa, 27
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
55, isa, 17
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
118, ingredient_of, 61
118, interacts_with, 47
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 27
111, isa, 17
66, affects, 28
66, affects, 124
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 17
66, isa, 55
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
Question: How are enzyme, organophosphorus_compound, and self_help_or_relief_organization related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"enzyme",
"organophosphorus_compound",
"self_help_or_relief_organization"
],
"valid_edges": [
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"enzyme",
"ingredient_of",
"clinical_drug"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"organophosphorus_compound",
"ingredient_of",
"clinical_drug"
],
[
"organophosphorus_compound",
"interacts_with",
"enzyme"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
48, classification
24, daily_or_recreational_activity
107, educational_activity
43, environmental_effect_of_humans
50, event
91, governmental_or_regulatory_activity
128, health_care_related_organization
70, idea_or_concept
55, intellectual_product
36, machine_activity
19, molecular_biology_research_technique
31, organization
41, professional_society
111, qualitative_concept
96, quantitative_concept
66, regulation_or_law
40, self_help_or_relief_organization
108, temporal_concept
src, edge_attr, dst
69, isa, 50
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
43, isa, 50
91, isa, 69
91, isa, 50
128, carries_out, 107
128, carries_out, 91
128, carries_out, 19
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 19
128, produces, 48
128, produces, 55
128, produces, 66
36, isa, 69
36, isa, 50
19, isa, 69
19, isa, 50
19, measures, 96
19, measures, 108
31, carries_out, 107
31, carries_out, 91
31, carries_out, 19
31, location_of, 107
31, location_of, 91
31, location_of, 19
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, carries_out, 19
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 19
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 69
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 36
111, evaluation_of, 19
111, isa, 70
96, isa, 70
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
40, carries_out, 107
40, carries_out, 91
40, carries_out, 19
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 19
40, produces, 48
40, produces, 55
40, produces, 66
108, isa, 70
Question: For what reason are environmental_effect_of_humans, machine_activity, and molecular_biology_research_technique associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"environmental_effect_of_humans",
"machine_activity",
"molecular_biology_research_technique"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"environmental_effect_of_humans",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"molecular_biology_research_technique"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"molecular_biology_research_technique"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"molecular_biology_research_technique",
"isa",
"activity"
],
[
"molecular_biology_research_technique",
"isa",
"event"
],
[
"molecular_biology_research_technique",
"measures",
"quantitative_concept"
],
[
"molecular_biology_research_technique",
"measures",
"temporal_concept"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"molecular_biology_research_technique"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"molecular_biology_research_technique"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"molecular_biology_research_technique"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"molecular_biology_research_technique"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"molecular_biology_research_technique"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"molecular_biology_research_technique"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"molecular_biology_research_technique"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
47, enzyme
16, group
58, occupation_or_discipline
src, edge_attr, dst
47, issue_in, 58
16, issue_in, 58
Question: How are enzyme, group, and occupation_or_discipline related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"enzyme",
"group",
"occupation_or_discipline"
],
"valid_edges": [
[
"enzyme",
"issue_in",
"occupation_or_discipline"
],
[
"group",
"issue_in",
"occupation_or_discipline"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
102, biologically_active_substance
123, diagnostic_procedure
31, organization
src, edge_attr, dst
123, analyzes, 102
123, assesses_effect_of, 102
123, measures, 102
31, carries_out, 123
31, location_of, 123
Question: In what context are biologically_active_substance, diagnostic_procedure, and organization connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biologically_active_substance",
"diagnostic_procedure",
"organization"
],
"valid_edges": [
[
"diagnostic_procedure",
"analyzes",
"biologically_active_substance"
],
[
"diagnostic_procedure",
"assesses_effect_of",
"biologically_active_substance"
],
[
"diagnostic_procedure",
"measures",
"biologically_active_substance"
],
[
"organization",
"carries_out",
"diagnostic_procedure"
],
[
"organization",
"location_of",
"diagnostic_procedure"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
32, molecular_sequence
58, occupation_or_discipline
71, phenomenon_or_process
src, edge_attr, dst
32, issue_in, 58
71, issue_in, 58
Question: For what reason are molecular_sequence, occupation_or_discipline, and phenomenon_or_process associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"molecular_sequence",
"occupation_or_discipline",
"phenomenon_or_process"
],
"valid_edges": [
[
"molecular_sequence",
"issue_in",
"occupation_or_discipline"
],
[
"phenomenon_or_process",
"issue_in",
"occupation_or_discipline"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
94, body_location_or_region
132, body_system
115, carbohydrate
106, cell_component
17, conceptual_entity
82, functional_concept
70, idea_or_concept
23, professional_or_occupational_group
src, edge_attr, dst
94, conceptual_part_of, 132
94, isa, 17
132, isa, 17
132, isa, 82
132, isa, 70
106, conceptual_part_of, 132
106, produces, 115
82, isa, 17
70, isa, 17
23, isa, 17
Question: In what context are carbohydrate, cell_component, and professional_or_occupational_group connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"carbohydrate",
"cell_component",
"professional_or_occupational_group"
],
"valid_edges": [
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"functional_concept"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"cell_component",
"conceptual_part_of",
"body_system"
],
[
"cell_component",
"produces",
"carbohydrate"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"professional_or_occupational_group",
"isa",
"conceptual_entity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
26, amino_acid_sequence
94, body_location_or_region
132, body_system
3, carbohydrate_sequence
48, classification
17, conceptual_entity
24, daily_or_recreational_activity
107, educational_activity
50, event
89, finding
82, functional_concept
42, geographic_area
91, governmental_or_regulatory_activity
128, health_care_related_organization
70, idea_or_concept
55, intellectual_product
85, laboratory_procedure
36, machine_activity
32, molecular_sequence
134, nucleotide_sequence
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
96, quantitative_concept
66, regulation_or_law
40, self_help_or_relief_organization
79, spatial_concept
108, temporal_concept
src, edge_attr, dst
69, isa, 50
26, isa, 17
26, isa, 70
26, isa, 32
26, isa, 79
94, isa, 17
94, isa, 70
94, isa, 79
132, isa, 17
132, isa, 70
3, isa, 17
3, isa, 70
3, isa, 32
3, isa, 79
48, isa, 17
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
107, isa, 27
89, isa, 17
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
42, isa, 79
91, isa, 69
91, isa, 50
91, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 85
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 85
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
70, isa, 17
55, isa, 17
85, isa, 69
85, isa, 50
85, isa, 27
85, measures, 96
85, measures, 108
36, isa, 69
36, isa, 50
36, method_of, 85
32, isa, 17
32, isa, 70
32, isa, 79
134, isa, 17
134, isa, 70
134, isa, 32
134, isa, 79
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 85
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 85
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, carries_out, 85
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 85
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 69
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 85
111, evaluation_of, 36
111, evaluation_of, 27
111, isa, 17
111, isa, 70
96, isa, 17
96, isa, 70
96, measurement_of, 26
96, measurement_of, 94
96, measurement_of, 3
96, measurement_of, 42
96, measurement_of, 32
96, measurement_of, 134
96, measurement_of, 79
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 17
40, carries_out, 107
40, carries_out, 91
40, carries_out, 85
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 85
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
79, isa, 17
79, isa, 70
108, isa, 17
108, isa, 70
Question: In what context are amino_acid_sequence, finding, and laboratory_procedure connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_sequence",
"finding",
"laboratory_procedure"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"amino_acid_sequence",
"isa",
"conceptual_entity"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"conceptual_entity"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"finding",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"laboratory_procedure"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"laboratory_procedure"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"laboratory_procedure",
"isa",
"activity"
],
[
"laboratory_procedure",
"isa",
"event"
],
[
"laboratory_procedure",
"isa",
"occupational_activity"
],
[
"laboratory_procedure",
"measures",
"quantitative_concept"
],
[
"laboratory_procedure",
"measures",
"temporal_concept"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"machine_activity",
"method_of",
"laboratory_procedure"
],
[
"molecular_sequence",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"laboratory_procedure"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"laboratory_procedure"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"laboratory_procedure"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"laboratory_procedure"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"laboratory_procedure"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"amino_acid_sequence"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"carbohydrate_sequence"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"quantitative_concept",
"measurement_of",
"molecular_sequence"
],
[
"quantitative_concept",
"measurement_of",
"nucleotide_sequence"
],
[
"quantitative_concept",
"measurement_of",
"spatial_concept"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"laboratory_procedure"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"laboratory_procedure"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"spatial_concept",
"isa",
"conceptual_entity"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"temporal_concept",
"isa",
"conceptual_entity"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
95, acquired_abnormality
69, activity
106, cell_component
48, classification
24, daily_or_recreational_activity
107, educational_activity
91, governmental_or_regulatory_activity
128, health_care_related_organization
55, intellectual_product
113, manufactured_object
31, organization
41, professional_society
111, qualitative_concept
66, regulation_or_law
67, research_device
40, self_help_or_relief_organization
src, edge_attr, dst
106, location_of, 95
48, isa, 55
24, associated_with, 95
24, isa, 69
107, associated_with, 95
107, isa, 69
91, associated_with, 95
91, isa, 69
128, carries_out, 107
128, carries_out, 91
128, isa, 31
128, location_of, 107
128, location_of, 91
128, produces, 48
128, produces, 55
128, produces, 66
113, causes, 95
31, carries_out, 107
31, carries_out, 91
31, location_of, 107
31, location_of, 91
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, isa, 31
41, location_of, 107
41, location_of, 91
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 55
67, causes, 95
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, isa, 31
40, location_of, 107
40, location_of, 91
40, produces, 48
40, produces, 55
40, produces, 66
Question: For what reason are acquired_abnormality, cell_component, and professional_society associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"acquired_abnormality",
"cell_component",
"professional_society"
],
"valid_edges": [
[
"cell_component",
"location_of",
"acquired_abnormality"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"daily_or_recreational_activity",
"associated_with",
"acquired_abnormality"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"educational_activity",
"associated_with",
"acquired_abnormality"
],
[
"educational_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"associated_with",
"acquired_abnormality"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"manufactured_object",
"causes",
"acquired_abnormality"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"causes",
"acquired_abnormality"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
42, geographic_area
70, idea_or_concept
52, laboratory_or_test_result
80, mental_or_behavioral_dysfunction
79, spatial_concept
108, temporal_concept
src, edge_attr, dst
42, associated_with, 80
42, isa, 70
42, isa, 79
52, associated_with, 80
52, evaluation_of, 80
52, indicates, 80
52, manifestation_of, 80
79, isa, 70
108, isa, 70
Question: For what reason are laboratory_or_test_result, mental_or_behavioral_dysfunction, and temporal_concept associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"laboratory_or_test_result",
"mental_or_behavioral_dysfunction",
"temporal_concept"
],
"valid_edges": [
[
"geographic_area",
"associated_with",
"mental_or_behavioral_dysfunction"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"laboratory_or_test_result",
"associated_with",
"mental_or_behavioral_dysfunction"
],
[
"laboratory_or_test_result",
"evaluation_of",
"mental_or_behavioral_dysfunction"
],
[
"laboratory_or_test_result",
"indicates",
"mental_or_behavioral_dysfunction"
],
[
"laboratory_or_test_result",
"manifestation_of",
"mental_or_behavioral_dysfunction"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
26, amino_acid_sequence
22, anatomical_structure
64, behavior
94, body_location_or_region
103, body_space_or_junction
132, body_system
3, carbohydrate_sequence
61, clinical_drug
17, conceptual_entity
88, embryonic_structure
50, event
75, food
82, functional_concept
42, geographic_area
10, group_attribute
99, hazardous_or_poisonous_substance
70, idea_or_concept
37, mammal
32, molecular_sequence
134, nucleotide_sequence
111, qualitative_concept
96, quantitative_concept
122, social_behavior
79, spatial_concept
84, substance
108, temporal_concept
src, edge_attr, dst
26, isa, 17
26, isa, 70
26, isa, 79
22, part_of, 37
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
94, adjacent_to, 103
94, conceptual_part_of, 132
94, isa, 17
94, isa, 70
94, isa, 79
103, conceptual_part_of, 132
103, isa, 17
103, isa, 70
103, isa, 79
132, isa, 17
132, isa, 82
132, isa, 70
3, isa, 17
3, isa, 70
3, isa, 79
88, isa, 22
88, part_of, 37
75, ingredient_of, 61
75, isa, 84
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
42, isa, 79
10, isa, 17
99, disrupts, 88
99, ingredient_of, 61
99, isa, 84
70, conceptual_part_of, 64
70, isa, 17
37, exhibits, 64
37, exhibits, 122
32, isa, 17
32, isa, 70
32, isa, 79
134, isa, 17
134, isa, 70
134, isa, 79
111, evaluation_of, 64
111, evaluation_of, 122
111, isa, 17
111, isa, 70
96, isa, 17
96, isa, 70
96, measurement_of, 26
96, measurement_of, 94
96, measurement_of, 103
96, measurement_of, 3
96, measurement_of, 42
96, measurement_of, 32
96, measurement_of, 134
96, measurement_of, 79
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
79, isa, 17
79, isa, 70
84, ingredient_of, 61
108, isa, 17
108, isa, 70
Question: For what reason are body_location_or_region, hazardous_or_poisonous_substance, and mammal associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_location_or_region",
"hazardous_or_poisonous_substance",
"mammal"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"conceptual_entity"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"anatomical_structure",
"part_of",
"mammal"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"body_location_or_region",
"adjacent_to",
"body_space_or_junction"
],
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_space_or_junction",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"isa",
"spatial_concept"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"functional_concept"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"conceptual_entity"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"part_of",
"mammal"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"hazardous_or_poisonous_substance",
"disrupts",
"embryonic_structure"
],
[
"hazardous_or_poisonous_substance",
"ingredient_of",
"clinical_drug"
],
[
"hazardous_or_poisonous_substance",
"isa",
"substance"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"mammal",
"exhibits",
"behavior"
],
[
"mammal",
"exhibits",
"social_behavior"
],
[
"molecular_sequence",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"amino_acid_sequence"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"body_space_or_junction"
],
[
"quantitative_concept",
"measurement_of",
"carbohydrate_sequence"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"quantitative_concept",
"measurement_of",
"molecular_sequence"
],
[
"quantitative_concept",
"measurement_of",
"nucleotide_sequence"
],
[
"quantitative_concept",
"measurement_of",
"spatial_concept"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"spatial_concept",
"isa",
"conceptual_entity"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"substance",
"ingredient_of",
"clinical_drug"
],
[
"temporal_concept",
"isa",
"conceptual_entity"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
130, bacterium
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
124, family_group
91, governmental_or_regulatory_activity
16, group
10, group_attribute
53, health_care_activity
128, health_care_related_organization
55, intellectual_product
85, laboratory_procedure
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
2, patient_or_disabled_group
126, physical_object
66, regulation_or_law
67, research_device
122, social_behavior
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, interacts_with, 16
28, interacts_with, 2
28, isa, 17
28, isa, 16
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 85
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
130, isa, 126
64, associated_with, 28
64, associated_with, 124
64, associated_with, 16
64, associated_with, 2
64, isa, 69
48, isa, 17
48, isa, 55
61, isa, 126
24, isa, 69
68, isa, 126
107, isa, 69
107, isa, 27
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, interacts_with, 16
124, interacts_with, 2
124, isa, 17
124, isa, 16
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 85
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
91, isa, 69
91, isa, 27
16, exhibits, 64
16, exhibits, 122
16, isa, 17
16, performs, 69
16, performs, 64
16, performs, 24
16, performs, 107
16, performs, 91
16, performs, 53
16, performs, 85
16, performs, 36
16, performs, 27
16, performs, 122
16, produces, 48
16, produces, 61
16, produces, 68
16, produces, 55
16, produces, 113
16, produces, 59
16, produces, 66
16, produces, 67
16, uses, 48
16, uses, 61
16, uses, 68
16, uses, 55
16, uses, 113
16, uses, 59
16, uses, 66
16, uses, 67
10, isa, 17
10, property_of, 28
10, property_of, 124
10, property_of, 16
10, property_of, 2
53, isa, 69
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 85
128, carries_out, 27
128, isa, 17
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 85
128, location_of, 27
128, manages, 2
128, produces, 48
128, produces, 55
128, produces, 66
55, isa, 17
85, isa, 69
85, isa, 53
85, isa, 27
36, isa, 69
36, method_of, 85
113, isa, 126
59, isa, 126
27, isa, 69
2, exhibits, 64
2, exhibits, 122
2, interacts_with, 16
2, isa, 17
2, isa, 16
2, performs, 69
2, performs, 64
2, performs, 24
2, performs, 107
2, performs, 91
2, performs, 53
2, performs, 85
2, performs, 36
2, performs, 27
2, performs, 122
2, produces, 48
2, produces, 61
2, produces, 68
2, produces, 55
2, produces, 113
2, produces, 59
2, produces, 66
2, produces, 67
2, uses, 48
2, uses, 61
2, uses, 68
2, uses, 55
2, uses, 113
2, uses, 59
2, uses, 66
2, uses, 67
66, affects, 28
66, affects, 124
66, affects, 16
66, affects, 128
66, affects, 2
66, isa, 17
66, isa, 55
67, isa, 126
122, associated_with, 28
122, associated_with, 124
122, associated_with, 16
122, associated_with, 2
122, isa, 69
Question: For what reason are bacterium, health_care_related_organization, and laboratory_procedure associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bacterium",
"health_care_related_organization",
"laboratory_procedure"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"interacts_with",
"group"
],
[
"age_group",
"interacts_with",
"patient_or_disabled_group"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"isa",
"group"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"laboratory_procedure"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"bacterium",
"isa",
"physical_object"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"group"
],
[
"behavior",
"associated_with",
"patient_or_disabled_group"
],
[
"behavior",
"isa",
"activity"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"clinical_drug",
"isa",
"physical_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"drug_delivery_device",
"isa",
"physical_object"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"interacts_with",
"group"
],
[
"family_group",
"interacts_with",
"patient_or_disabled_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"isa",
"group"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"laboratory_procedure"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group",
"exhibits",
"behavior"
],
[
"group",
"exhibits",
"social_behavior"
],
[
"group",
"isa",
"conceptual_entity"
],
[
"group",
"performs",
"activity"
],
[
"group",
"performs",
"behavior"
],
[
"group",
"performs",
"daily_or_recreational_activity"
],
[
"group",
"performs",
"educational_activity"
],
[
"group",
"performs",
"governmental_or_regulatory_activity"
],
[
"group",
"performs",
"health_care_activity"
],
[
"group",
"performs",
"laboratory_procedure"
],
[
"group",
"performs",
"machine_activity"
],
[
"group",
"performs",
"occupational_activity"
],
[
"group",
"performs",
"social_behavior"
],
[
"group",
"produces",
"classification"
],
[
"group",
"produces",
"clinical_drug"
],
[
"group",
"produces",
"drug_delivery_device"
],
[
"group",
"produces",
"intellectual_product"
],
[
"group",
"produces",
"manufactured_object"
],
[
"group",
"produces",
"medical_device"
],
[
"group",
"produces",
"regulation_or_law"
],
[
"group",
"produces",
"research_device"
],
[
"group",
"uses",
"classification"
],
[
"group",
"uses",
"clinical_drug"
],
[
"group",
"uses",
"drug_delivery_device"
],
[
"group",
"uses",
"intellectual_product"
],
[
"group",
"uses",
"manufactured_object"
],
[
"group",
"uses",
"medical_device"
],
[
"group",
"uses",
"regulation_or_law"
],
[
"group",
"uses",
"research_device"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"group_attribute",
"property_of",
"group"
],
[
"group_attribute",
"property_of",
"patient_or_disabled_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"laboratory_procedure"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"laboratory_procedure"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"manages",
"patient_or_disabled_group"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"laboratory_procedure",
"isa",
"activity"
],
[
"laboratory_procedure",
"isa",
"health_care_activity"
],
[
"laboratory_procedure",
"isa",
"occupational_activity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"method_of",
"laboratory_procedure"
],
[
"manufactured_object",
"isa",
"physical_object"
],
[
"medical_device",
"isa",
"physical_object"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"patient_or_disabled_group",
"exhibits",
"behavior"
],
[
"patient_or_disabled_group",
"exhibits",
"social_behavior"
],
[
"patient_or_disabled_group",
"interacts_with",
"group"
],
[
"patient_or_disabled_group",
"isa",
"conceptual_entity"
],
[
"patient_or_disabled_group",
"isa",
"group"
],
[
"patient_or_disabled_group",
"performs",
"activity"
],
[
"patient_or_disabled_group",
"performs",
"behavior"
],
[
"patient_or_disabled_group",
"performs",
"daily_or_recreational_activity"
],
[
"patient_or_disabled_group",
"performs",
"educational_activity"
],
[
"patient_or_disabled_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"patient_or_disabled_group",
"performs",
"health_care_activity"
],
[
"patient_or_disabled_group",
"performs",
"laboratory_procedure"
],
[
"patient_or_disabled_group",
"performs",
"machine_activity"
],
[
"patient_or_disabled_group",
"performs",
"occupational_activity"
],
[
"patient_or_disabled_group",
"performs",
"social_behavior"
],
[
"patient_or_disabled_group",
"produces",
"classification"
],
[
"patient_or_disabled_group",
"produces",
"clinical_drug"
],
[
"patient_or_disabled_group",
"produces",
"drug_delivery_device"
],
[
"patient_or_disabled_group",
"produces",
"intellectual_product"
],
[
"patient_or_disabled_group",
"produces",
"manufactured_object"
],
[
"patient_or_disabled_group",
"produces",
"medical_device"
],
[
"patient_or_disabled_group",
"produces",
"regulation_or_law"
],
[
"patient_or_disabled_group",
"produces",
"research_device"
],
[
"patient_or_disabled_group",
"uses",
"classification"
],
[
"patient_or_disabled_group",
"uses",
"clinical_drug"
],
[
"patient_or_disabled_group",
"uses",
"drug_delivery_device"
],
[
"patient_or_disabled_group",
"uses",
"intellectual_product"
],
[
"patient_or_disabled_group",
"uses",
"manufactured_object"
],
[
"patient_or_disabled_group",
"uses",
"medical_device"
],
[
"patient_or_disabled_group",
"uses",
"regulation_or_law"
],
[
"patient_or_disabled_group",
"uses",
"research_device"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"group"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"patient_or_disabled_group"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"isa",
"physical_object"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"group"
],
[
"social_behavior",
"associated_with",
"patient_or_disabled_group"
],
[
"social_behavior",
"isa",
"activity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
112, alga
22, anatomical_structure
73, archaeon
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
88, embryonic_structure
124, family_group
75, food
91, governmental_or_regulatory_activity
16, group
10, group_attribute
53, health_care_activity
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
118, organophosphorus_compound
2, patient_or_disabled_group
126, physical_object
66, regulation_or_law
67, research_device
122, social_behavior
84, substance
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, interacts_with, 16
28, interacts_with, 2
28, isa, 17
28, isa, 16
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
112, interacts_with, 73
112, isa, 126
22, isa, 126
22, part_of, 112
22, part_of, 73
73, isa, 126
64, associated_with, 28
64, associated_with, 124
64, associated_with, 16
64, associated_with, 2
61, isa, 113
61, isa, 126
68, contains, 61
68, isa, 113
68, isa, 59
68, isa, 126
88, isa, 22
88, isa, 126
88, part_of, 112
88, part_of, 73
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, interacts_with, 16
124, interacts_with, 2
124, isa, 17
124, isa, 16
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
75, ingredient_of, 61
75, isa, 126
75, isa, 84
16, exhibits, 64
16, exhibits, 122
16, isa, 17
16, performs, 69
16, performs, 64
16, performs, 24
16, performs, 107
16, performs, 91
16, performs, 53
16, performs, 36
16, performs, 27
16, performs, 122
16, produces, 48
16, produces, 61
16, produces, 68
16, produces, 55
16, produces, 113
16, produces, 59
16, produces, 66
16, produces, 67
16, uses, 48
16, uses, 61
16, uses, 68
16, uses, 55
16, uses, 113
16, uses, 59
16, uses, 66
16, uses, 67
10, property_of, 28
10, property_of, 124
10, property_of, 16
10, property_of, 2
113, isa, 126
59, isa, 113
59, isa, 126
118, ingredient_of, 61
118, isa, 126
118, isa, 84
2, exhibits, 64
2, exhibits, 122
2, interacts_with, 16
2, isa, 17
2, isa, 16
2, performs, 69
2, performs, 64
2, performs, 24
2, performs, 107
2, performs, 91
2, performs, 53
2, performs, 36
2, performs, 27
2, performs, 122
2, produces, 48
2, produces, 61
2, produces, 68
2, produces, 55
2, produces, 113
2, produces, 59
2, produces, 66
2, produces, 67
2, uses, 48
2, uses, 61
2, uses, 68
2, uses, 55
2, uses, 113
2, uses, 59
2, uses, 66
2, uses, 67
66, affects, 28
66, affects, 124
66, affects, 16
66, affects, 2
67, isa, 113
67, isa, 126
122, associated_with, 28
122, associated_with, 124
122, associated_with, 16
122, associated_with, 2
84, ingredient_of, 61
84, isa, 126
Question: How are alga, medical_device, and organophosphorus_compound related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"alga",
"medical_device",
"organophosphorus_compound"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"interacts_with",
"group"
],
[
"age_group",
"interacts_with",
"patient_or_disabled_group"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"isa",
"group"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"alga",
"interacts_with",
"archaeon"
],
[
"alga",
"isa",
"physical_object"
],
[
"anatomical_structure",
"isa",
"physical_object"
],
[
"anatomical_structure",
"part_of",
"alga"
],
[
"anatomical_structure",
"part_of",
"archaeon"
],
[
"archaeon",
"isa",
"physical_object"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"group"
],
[
"behavior",
"associated_with",
"patient_or_disabled_group"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"clinical_drug",
"isa",
"physical_object"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"drug_delivery_device",
"isa",
"physical_object"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"isa",
"physical_object"
],
[
"embryonic_structure",
"part_of",
"alga"
],
[
"embryonic_structure",
"part_of",
"archaeon"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"interacts_with",
"group"
],
[
"family_group",
"interacts_with",
"patient_or_disabled_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"isa",
"group"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"physical_object"
],
[
"food",
"isa",
"substance"
],
[
"group",
"exhibits",
"behavior"
],
[
"group",
"exhibits",
"social_behavior"
],
[
"group",
"isa",
"conceptual_entity"
],
[
"group",
"performs",
"activity"
],
[
"group",
"performs",
"behavior"
],
[
"group",
"performs",
"daily_or_recreational_activity"
],
[
"group",
"performs",
"educational_activity"
],
[
"group",
"performs",
"governmental_or_regulatory_activity"
],
[
"group",
"performs",
"health_care_activity"
],
[
"group",
"performs",
"machine_activity"
],
[
"group",
"performs",
"occupational_activity"
],
[
"group",
"performs",
"social_behavior"
],
[
"group",
"produces",
"classification"
],
[
"group",
"produces",
"clinical_drug"
],
[
"group",
"produces",
"drug_delivery_device"
],
[
"group",
"produces",
"intellectual_product"
],
[
"group",
"produces",
"manufactured_object"
],
[
"group",
"produces",
"medical_device"
],
[
"group",
"produces",
"regulation_or_law"
],
[
"group",
"produces",
"research_device"
],
[
"group",
"uses",
"classification"
],
[
"group",
"uses",
"clinical_drug"
],
[
"group",
"uses",
"drug_delivery_device"
],
[
"group",
"uses",
"intellectual_product"
],
[
"group",
"uses",
"manufactured_object"
],
[
"group",
"uses",
"medical_device"
],
[
"group",
"uses",
"regulation_or_law"
],
[
"group",
"uses",
"research_device"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"group_attribute",
"property_of",
"group"
],
[
"group_attribute",
"property_of",
"patient_or_disabled_group"
],
[
"manufactured_object",
"isa",
"physical_object"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"medical_device",
"isa",
"physical_object"
],
[
"organophosphorus_compound",
"ingredient_of",
"clinical_drug"
],
[
"organophosphorus_compound",
"isa",
"physical_object"
],
[
"organophosphorus_compound",
"isa",
"substance"
],
[
"patient_or_disabled_group",
"exhibits",
"behavior"
],
[
"patient_or_disabled_group",
"exhibits",
"social_behavior"
],
[
"patient_or_disabled_group",
"interacts_with",
"group"
],
[
"patient_or_disabled_group",
"isa",
"conceptual_entity"
],
[
"patient_or_disabled_group",
"isa",
"group"
],
[
"patient_or_disabled_group",
"performs",
"activity"
],
[
"patient_or_disabled_group",
"performs",
"behavior"
],
[
"patient_or_disabled_group",
"performs",
"daily_or_recreational_activity"
],
[
"patient_or_disabled_group",
"performs",
"educational_activity"
],
[
"patient_or_disabled_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"patient_or_disabled_group",
"performs",
"health_care_activity"
],
[
"patient_or_disabled_group",
"performs",
"machine_activity"
],
[
"patient_or_disabled_group",
"performs",
"occupational_activity"
],
[
"patient_or_disabled_group",
"performs",
"social_behavior"
],
[
"patient_or_disabled_group",
"produces",
"classification"
],
[
"patient_or_disabled_group",
"produces",
"clinical_drug"
],
[
"patient_or_disabled_group",
"produces",
"drug_delivery_device"
],
[
"patient_or_disabled_group",
"produces",
"intellectual_product"
],
[
"patient_or_disabled_group",
"produces",
"manufactured_object"
],
[
"patient_or_disabled_group",
"produces",
"medical_device"
],
[
"patient_or_disabled_group",
"produces",
"regulation_or_law"
],
[
"patient_or_disabled_group",
"produces",
"research_device"
],
[
"patient_or_disabled_group",
"uses",
"classification"
],
[
"patient_or_disabled_group",
"uses",
"clinical_drug"
],
[
"patient_or_disabled_group",
"uses",
"drug_delivery_device"
],
[
"patient_or_disabled_group",
"uses",
"intellectual_product"
],
[
"patient_or_disabled_group",
"uses",
"manufactured_object"
],
[
"patient_or_disabled_group",
"uses",
"medical_device"
],
[
"patient_or_disabled_group",
"uses",
"regulation_or_law"
],
[
"patient_or_disabled_group",
"uses",
"research_device"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"group"
],
[
"regulation_or_law",
"affects",
"patient_or_disabled_group"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"research_device",
"isa",
"physical_object"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"group"
],
[
"social_behavior",
"associated_with",
"patient_or_disabled_group"
],
[
"substance",
"ingredient_of",
"clinical_drug"
],
[
"substance",
"isa",
"physical_object"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
22, anatomical_structure
127, animal
64, behavior
94, body_location_or_region
103, body_space_or_junction
132, body_system
92, cell
8, chemical_viewed_functionally
61, clinical_drug
17, conceptual_entity
88, embryonic_structure
50, event
124, family_group
42, geographic_area
10, group_attribute
70, idea_or_concept
111, qualitative_concept
122, social_behavior
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, performs, 64
28, performs, 122
28, produces, 61
28, uses, 61
22, part_of, 127
127, exhibits, 64
127, exhibits, 122
64, affects, 122
64, associated_with, 28
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
94, adjacent_to, 103
94, conceptual_part_of, 132
103, conceptual_part_of, 132
103, interconnects, 92
103, isa, 17
103, isa, 70
103, surrounds, 92
132, isa, 17
132, isa, 70
92, conceptual_part_of, 132
92, isa, 22
92, location_of, 103
92, part_of, 127
8, ingredient_of, 61
88, developmental_form_of, 92
88, isa, 22
88, part_of, 127
88, part_of, 92
88, surrounds, 92
124, exhibits, 64
124, exhibits, 122
124, performs, 64
124, performs, 122
124, produces, 61
124, uses, 61
70, conceptual_part_of, 64
111, evaluation_of, 64
111, evaluation_of, 122
122, affects, 64
122, associated_with, 28
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: How are animal, cell, and chemical_viewed_functionally related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"animal",
"cell",
"chemical_viewed_functionally"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"anatomical_structure",
"part_of",
"animal"
],
[
"animal",
"exhibits",
"behavior"
],
[
"animal",
"exhibits",
"social_behavior"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"body_location_or_region",
"adjacent_to",
"body_space_or_junction"
],
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"interconnects",
"cell"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"surrounds",
"cell"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"cell",
"conceptual_part_of",
"body_system"
],
[
"cell",
"isa",
"anatomical_structure"
],
[
"cell",
"location_of",
"body_space_or_junction"
],
[
"cell",
"part_of",
"animal"
],
[
"chemical_viewed_functionally",
"ingredient_of",
"clinical_drug"
],
[
"embryonic_structure",
"developmental_form_of",
"cell"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"part_of",
"animal"
],
[
"embryonic_structure",
"part_of",
"cell"
],
[
"embryonic_structure",
"surrounds",
"cell"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
47, enzyme
74, invertebrate
18, physiologic_function
src, edge_attr, dst
47, affects, 18
47, complicates, 18
47, disrupts, 18
18, affects, 74
18, process_of, 74
18, produces, 47
Question: In what context are enzyme, invertebrate, and physiologic_function connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"enzyme",
"invertebrate",
"physiologic_function"
],
"valid_edges": [
[
"enzyme",
"affects",
"physiologic_function"
],
[
"enzyme",
"complicates",
"physiologic_function"
],
[
"enzyme",
"disrupts",
"physiologic_function"
],
[
"physiologic_function",
"affects",
"invertebrate"
],
[
"physiologic_function",
"process_of",
"invertebrate"
],
[
"physiologic_function",
"produces",
"enzyme"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
95, acquired_abnormality
26, amino_acid_sequence
3, carbohydrate_sequence
24, daily_or_recreational_activity
42, geographic_area
70, idea_or_concept
36, machine_activity
32, molecular_sequence
134, nucleotide_sequence
1, population_group
111, qualitative_concept
79, spatial_concept
src, edge_attr, dst
95, occurs_in, 1
26, isa, 70
26, isa, 32
26, isa, 79
3, isa, 70
3, isa, 32
3, isa, 79
24, associated_with, 95
42, associated_with, 95
42, isa, 70
42, isa, 79
32, isa, 70
32, isa, 79
134, isa, 70
134, isa, 32
134, isa, 79
1, associated_with, 95
1, performs, 24
1, performs, 36
111, evaluation_of, 24
111, evaluation_of, 36
111, isa, 70
79, isa, 70
Question: For what reason are acquired_abnormality, amino_acid_sequence, and population_group associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"acquired_abnormality",
"amino_acid_sequence",
"population_group"
],
"valid_edges": [
[
"acquired_abnormality",
"occurs_in",
"population_group"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"daily_or_recreational_activity",
"associated_with",
"acquired_abnormality"
],
[
"geographic_area",
"associated_with",
"acquired_abnormality"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"population_group",
"associated_with",
"acquired_abnormality"
],
[
"population_group",
"performs",
"daily_or_recreational_activity"
],
[
"population_group",
"performs",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
28, age_group
3, carbohydrate_sequence
24, daily_or_recreational_activity
70, idea_or_concept
36, machine_activity
111, qualitative_concept
79, spatial_concept
src, edge_attr, dst
28, performs, 24
28, performs, 36
3, isa, 70
3, isa, 79
111, evaluation_of, 24
111, evaluation_of, 36
111, isa, 70
79, isa, 70
Question: For what reason are age_group, carbohydrate_sequence, and spatial_concept associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"age_group",
"carbohydrate_sequence",
"spatial_concept"
],
"valid_edges": [
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
62, disease_or_syndrome
58, occupation_or_discipline
20, steroid
src, edge_attr, dst
62, issue_in, 58
20, affects, 62
20, causes, 62
20, issue_in, 58
Question: For what reason are disease_or_syndrome, occupation_or_discipline, and steroid associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"disease_or_syndrome",
"occupation_or_discipline",
"steroid"
],
"valid_edges": [
[
"disease_or_syndrome",
"issue_in",
"occupation_or_discipline"
],
[
"steroid",
"affects",
"disease_or_syndrome"
],
[
"steroid",
"causes",
"disease_or_syndrome"
],
[
"steroid",
"issue_in",
"occupation_or_discipline"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
63, lipid
87, plant
0, vitamin
src, edge_attr, dst
63, interacts_with, 0
87, location_of, 0
Question: How are lipid, plant, and vitamin related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"lipid",
"plant",
"vitamin"
],
"valid_edges": [
[
"lipid",
"interacts_with",
"vitamin"
],
[
"plant",
"location_of",
"vitamin"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
95, acquired_abnormality
69, activity
48, classification
24, daily_or_recreational_activity
107, educational_activity
91, governmental_or_regulatory_activity
128, health_care_related_organization
55, intellectual_product
113, manufactured_object
31, organization
41, professional_society
111, qualitative_concept
66, regulation_or_law
67, research_device
40, self_help_or_relief_organization
101, sign_or_symptom
src, edge_attr, dst
48, isa, 55
24, associated_with, 95
24, isa, 69
107, associated_with, 95
107, isa, 69
91, associated_with, 95
91, isa, 69
128, carries_out, 107
128, carries_out, 91
128, isa, 31
128, location_of, 107
128, location_of, 91
128, produces, 48
128, produces, 55
128, produces, 66
113, causes, 95
31, carries_out, 107
31, carries_out, 91
31, location_of, 107
31, location_of, 91
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, isa, 31
41, location_of, 107
41, location_of, 91
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 55
67, causes, 95
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, isa, 31
40, location_of, 107
40, location_of, 91
40, produces, 48
40, produces, 55
40, produces, 66
101, associated_with, 95
101, diagnoses, 95
101, manifestation_of, 95
Question: In what context are acquired_abnormality, self_help_or_relief_organization, and sign_or_symptom connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"acquired_abnormality",
"self_help_or_relief_organization",
"sign_or_symptom"
],
"valid_edges": [
[
"classification",
"isa",
"intellectual_product"
],
[
"daily_or_recreational_activity",
"associated_with",
"acquired_abnormality"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"educational_activity",
"associated_with",
"acquired_abnormality"
],
[
"educational_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"associated_with",
"acquired_abnormality"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"manufactured_object",
"causes",
"acquired_abnormality"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"causes",
"acquired_abnormality"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"sign_or_symptom",
"associated_with",
"acquired_abnormality"
],
[
"sign_or_symptom",
"diagnoses",
"acquired_abnormality"
],
[
"sign_or_symptom",
"manifestation_of",
"acquired_abnormality"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
95, acquired_abnormality
57, amino_acid_peptide_or_protein
33, eicosanoid
src, edge_attr, dst
57, causes, 95
57, interacts_with, 33
33, causes, 95
Question: For what reason are acquired_abnormality, amino_acid_peptide_or_protein, and eicosanoid associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"acquired_abnormality",
"amino_acid_peptide_or_protein",
"eicosanoid"
],
"valid_edges": [
[
"amino_acid_peptide_or_protein",
"causes",
"acquired_abnormality"
],
[
"amino_acid_peptide_or_protein",
"interacts_with",
"eicosanoid"
],
[
"eicosanoid",
"causes",
"acquired_abnormality"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
22, anatomical_structure
64, behavior
17, conceptual_entity
24, daily_or_recreational_activity
107, educational_activity
88, embryonic_structure
50, event
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
70, idea_or_concept
36, machine_activity
37, mammal
27, occupational_activity
111, qualitative_concept
93, rickettsia_or_chlamydia
122, social_behavior
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
22, location_of, 93
22, part_of, 37
22, part_of, 93
64, affects, 122
64, associated_with, 28
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
107, isa, 27
88, isa, 22
88, location_of, 93
88, part_of, 37
88, part_of, 93
42, isa, 17
91, isa, 69
91, isa, 50
91, isa, 27
10, isa, 17
10, property_of, 28
53, isa, 69
53, isa, 50
53, isa, 27
70, conceptual_part_of, 64
70, isa, 17
36, isa, 69
36, isa, 50
37, exhibits, 64
37, exhibits, 122
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
93, interacts_with, 37
122, affects, 64
122, associated_with, 28
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: For what reason are age_group, mammal, and rickettsia_or_chlamydia associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"age_group",
"mammal",
"rickettsia_or_chlamydia"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"anatomical_structure",
"location_of",
"rickettsia_or_chlamydia"
],
[
"anatomical_structure",
"part_of",
"mammal"
],
[
"anatomical_structure",
"part_of",
"rickettsia_or_chlamydia"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"location_of",
"rickettsia_or_chlamydia"
],
[
"embryonic_structure",
"part_of",
"mammal"
],
[
"embryonic_structure",
"part_of",
"rickettsia_or_chlamydia"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"mammal",
"exhibits",
"behavior"
],
[
"mammal",
"exhibits",
"social_behavior"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"rickettsia_or_chlamydia",
"interacts_with",
"mammal"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
112, alga
98, pathologic_function
114, vertebrate
src, edge_attr, dst
112, interacts_with, 114
98, affects, 112
98, affects, 114
98, process_of, 112
98, process_of, 114
Question: For what reason are alga, pathologic_function, and vertebrate associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"alga",
"pathologic_function",
"vertebrate"
],
"valid_edges": [
[
"alga",
"interacts_with",
"vertebrate"
],
[
"pathologic_function",
"affects",
"alga"
],
[
"pathologic_function",
"affects",
"vertebrate"
],
[
"pathologic_function",
"process_of",
"alga"
],
[
"pathologic_function",
"process_of",
"vertebrate"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
73, archaeon
49, clinical_attribute
17, conceptual_entity
10, group_attribute
src, edge_attr, dst
49, isa, 17
49, property_of, 73
10, isa, 17
Question: How are archaeon, clinical_attribute, and group_attribute related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"archaeon",
"clinical_attribute",
"group_attribute"
],
"valid_edges": [
[
"clinical_attribute",
"isa",
"conceptual_entity"
],
[
"clinical_attribute",
"property_of",
"archaeon"
],
[
"group_attribute",
"isa",
"conceptual_entity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
28, age_group
94, body_location_or_region
61, clinical_drug
17, conceptual_entity
124, family_group
42, geographic_area
70, idea_or_concept
34, immunologic_factor
77, neuroreactive_substance_or_biogenic_amine
111, qualitative_concept
src, edge_attr, dst
28, isa, 17
28, produces, 61
28, uses, 61
94, isa, 17
94, isa, 70
124, isa, 17
124, produces, 61
124, uses, 61
42, isa, 17
42, isa, 70
70, isa, 17
34, ingredient_of, 61
77, ingredient_of, 61
77, interacts_with, 34
111, isa, 17
111, isa, 70
Question: For what reason are body_location_or_region, immunologic_factor, and neuroreactive_substance_or_biogenic_amine associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_location_or_region",
"immunologic_factor",
"neuroreactive_substance_or_biogenic_amine"
],
"valid_edges": [
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"immunologic_factor",
"ingredient_of",
"clinical_drug"
],
[
"neuroreactive_substance_or_biogenic_amine",
"ingredient_of",
"clinical_drug"
],
[
"neuroreactive_substance_or_biogenic_amine",
"interacts_with",
"immunologic_factor"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
14, inorganic_chemical
77, neuroreactive_substance_or_biogenic_amine
125, nucleic_acid_nucleoside_or_nucleotide
src, edge_attr, dst
14, interacts_with, 77
125, interacts_with, 14
125, interacts_with, 77
Question: For what reason are inorganic_chemical, neuroreactive_substance_or_biogenic_amine, and nucleic_acid_nucleoside_or_nucleotide associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"inorganic_chemical",
"neuroreactive_substance_or_biogenic_amine",
"nucleic_acid_nucleoside_or_nucleotide"
],
"valid_edges": [
[
"inorganic_chemical",
"interacts_with",
"neuroreactive_substance_or_biogenic_amine"
],
[
"nucleic_acid_nucleoside_or_nucleotide",
"interacts_with",
"inorganic_chemical"
],
[
"nucleic_acid_nucleoside_or_nucleotide",
"interacts_with",
"neuroreactive_substance_or_biogenic_amine"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
121, biomedical_or_dental_material
37, mammal
51, organism_function
src, edge_attr, dst
121, affects, 51
51, affects, 37
51, process_of, 37
Question: For what reason are biomedical_or_dental_material, mammal, and organism_function associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biomedical_or_dental_material",
"mammal",
"organism_function"
],
"valid_edges": [
[
"biomedical_or_dental_material",
"affects",
"organism_function"
],
[
"organism_function",
"affects",
"mammal"
],
[
"organism_function",
"process_of",
"mammal"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
11, cell_or_molecular_dysfunction
39, research_activity
7, therapeutic_or_preventive_procedure
src, edge_attr, dst
11, result_of, 7
39, associated_with, 11
39, measures, 11
7, affects, 11
7, associated_with, 11
7, complicates, 11
7, prevents, 11
7, treats, 11
Question: In what context are cell_or_molecular_dysfunction, research_activity, and therapeutic_or_preventive_procedure connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"cell_or_molecular_dysfunction",
"research_activity",
"therapeutic_or_preventive_procedure"
],
"valid_edges": [
[
"cell_or_molecular_dysfunction",
"result_of",
"therapeutic_or_preventive_procedure"
],
[
"research_activity",
"associated_with",
"cell_or_molecular_dysfunction"
],
[
"research_activity",
"measures",
"cell_or_molecular_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"affects",
"cell_or_molecular_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"associated_with",
"cell_or_molecular_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"complicates",
"cell_or_molecular_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"prevents",
"cell_or_molecular_dysfunction"
],
[
"therapeutic_or_preventive_procedure",
"treats",
"cell_or_molecular_dysfunction"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
50, event
124, family_group
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
70, idea_or_concept
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
66, regulation_or_law
67, research_device
40, self_help_or_relief_organization
122, social_behavior
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
64, associated_with, 28
64, associated_with, 124
64, isa, 69
64, isa, 50
48, isa, 17
48, isa, 55
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
68, isa, 113
68, isa, 59
107, isa, 69
107, isa, 50
107, isa, 27
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
91, isa, 69
91, isa, 50
91, isa, 27
10, isa, 17
10, property_of, 28
10, property_of, 124
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
70, isa, 17
55, isa, 17
36, isa, 69
36, isa, 50
59, isa, 113
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
66, affects, 28
66, affects, 124
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 17
66, isa, 55
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
122, associated_with, 28
122, associated_with, 124
122, isa, 69
122, isa, 50
Question: For what reason are drug_delivery_device, educational_activity, and professional_society associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"drug_delivery_device",
"educational_activity",
"professional_society"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
64, behavior
17, conceptual_entity
50, event
42, geographic_area
10, group_attribute
70, idea_or_concept
52, laboratory_or_test_result
37, mammal
111, qualitative_concept
122, social_behavior
114, vertebrate
src, edge_attr, dst
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
42, isa, 17
10, isa, 17
70, conceptual_part_of, 64
70, isa, 17
52, isa, 17
37, exhibits, 64
37, exhibits, 122
37, isa, 114
111, evaluation_of, 64
111, evaluation_of, 122
111, isa, 17
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
114, exhibits, 64
114, exhibits, 122
114, interacts_with, 37
Question: How are laboratory_or_test_result, mammal, and vertebrate related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"laboratory_or_test_result",
"mammal",
"vertebrate"
],
"valid_edges": [
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"laboratory_or_test_result",
"isa",
"conceptual_entity"
],
[
"mammal",
"exhibits",
"behavior"
],
[
"mammal",
"exhibits",
"social_behavior"
],
[
"mammal",
"isa",
"vertebrate"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"vertebrate",
"exhibits",
"behavior"
],
[
"vertebrate",
"exhibits",
"social_behavior"
],
[
"vertebrate",
"interacts_with",
"mammal"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
26, amino_acid_sequence
127, animal
64, behavior
94, body_location_or_region
103, body_space_or_junction
132, body_system
3, carbohydrate_sequence
17, conceptual_entity
107, educational_activity
50, event
82, functional_concept
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
70, idea_or_concept
32, molecular_sequence
134, nucleotide_sequence
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
96, quantitative_concept
40, self_help_or_relief_organization
101, sign_or_symptom
122, social_behavior
79, spatial_concept
108, temporal_concept
src, edge_attr, dst
26, isa, 17
26, isa, 70
26, isa, 32
26, isa, 79
127, exhibits, 64
127, exhibits, 122
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
94, adjacent_to, 103
94, conceptual_part_of, 132
94, isa, 17
94, isa, 70
94, isa, 79
103, conceptual_part_of, 132
103, isa, 17
103, isa, 70
103, isa, 79
132, isa, 17
132, isa, 82
132, isa, 70
3, isa, 17
3, isa, 70
3, isa, 32
3, isa, 79
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
42, isa, 79
10, isa, 17
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
70, conceptual_part_of, 64
70, isa, 17
32, isa, 17
32, isa, 70
32, isa, 79
134, isa, 17
134, isa, 70
134, isa, 32
134, isa, 79
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
96, isa, 17
96, isa, 70
96, measurement_of, 26
96, measurement_of, 94
96, measurement_of, 103
96, measurement_of, 3
96, measurement_of, 42
96, measurement_of, 32
96, measurement_of, 134
96, measurement_of, 79
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
101, isa, 17
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
79, isa, 17
79, isa, 70
108, isa, 17
108, isa, 70
Question: For what reason are animal, conceptual_entity, and sign_or_symptom associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"animal",
"conceptual_entity",
"sign_or_symptom"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"conceptual_entity"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"animal",
"exhibits",
"behavior"
],
[
"animal",
"exhibits",
"social_behavior"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"body_location_or_region",
"adjacent_to",
"body_space_or_junction"
],
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_space_or_junction",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"isa",
"spatial_concept"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"functional_concept"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"conceptual_entity"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"amino_acid_sequence"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"body_space_or_junction"
],
[
"quantitative_concept",
"measurement_of",
"carbohydrate_sequence"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"quantitative_concept",
"measurement_of",
"molecular_sequence"
],
[
"quantitative_concept",
"measurement_of",
"nucleotide_sequence"
],
[
"quantitative_concept",
"measurement_of",
"spatial_concept"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"sign_or_symptom",
"isa",
"conceptual_entity"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"spatial_concept",
"isa",
"conceptual_entity"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"temporal_concept",
"isa",
"conceptual_entity"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
94, body_location_or_region
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
107, educational_activity
50, event
124, family_group
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
70, idea_or_concept
36, machine_activity
27, occupational_activity
31, organization
72, pharmacologic_substance
41, professional_society
111, qualitative_concept
40, self_help_or_relief_organization
122, social_behavior
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 61
28, uses, 61
64, affects, 122
64, associated_with, 28
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
94, isa, 17
94, isa, 70
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
107, isa, 27
124, exhibits, 64
124, exhibits, 122
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 61
124, uses, 61
42, isa, 17
42, isa, 70
91, isa, 69
91, isa, 50
91, isa, 27
10, isa, 17
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
70, conceptual_part_of, 64
70, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
72, ingredient_of, 61
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
122, affects, 64
122, associated_with, 28
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: How are body_location_or_region, pharmacologic_substance, and qualitative_concept related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_location_or_region",
"pharmacologic_substance",
"qualitative_concept"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"pharmacologic_substance",
"ingredient_of",
"clinical_drug"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
17, conceptual_entity
24, daily_or_recreational_activity
107, educational_activity
50, event
89, finding
91, governmental_or_regulatory_activity
10, group_attribute
70, idea_or_concept
36, machine_activity
27, occupational_activity
111, qualitative_concept
src, edge_attr, dst
69, isa, 50
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
89, isa, 17
91, isa, 69
91, isa, 50
10, isa, 17
70, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 36
111, evaluation_of, 27
111, isa, 17
111, isa, 70
Question: In what context are finding, group_attribute, and machine_activity connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"finding",
"group_attribute",
"machine_activity"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"finding",
"isa",
"conceptual_entity"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
48, classification
49, clinical_attribute
61, clinical_drug
17, conceptual_entity
107, educational_activity
50, event
124, family_group
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
70, idea_or_concept
55, intellectual_product
27, occupational_activity
31, organization
72, pharmacologic_substance
41, professional_society
111, qualitative_concept
66, regulation_or_law
40, self_help_or_relief_organization
122, social_behavior
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 64
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 55
28, produces, 66
28, uses, 48
28, uses, 61
28, uses, 55
28, uses, 66
64, affects, 122
64, associated_with, 28
64, associated_with, 49
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
48, isa, 17
48, isa, 55
49, isa, 17
107, isa, 69
107, isa, 50
107, isa, 27
124, exhibits, 64
124, exhibits, 122
124, isa, 17
124, performs, 64
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 55
124, produces, 66
124, uses, 48
124, uses, 61
124, uses, 55
124, uses, 66
42, isa, 17
91, isa, 69
91, isa, 50
91, isa, 27
10, isa, 17
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
70, conceptual_part_of, 64
70, isa, 17
55, isa, 17
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
72, ingredient_of, 61
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 64
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
66, affects, 28
66, affects, 124
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 17
66, isa, 55
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
122, affects, 64
122, associated_with, 28
122, associated_with, 49
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: How are clinical_attribute, organization, and pharmacologic_substance related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"clinical_attribute",
"organization",
"pharmacologic_substance"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"clinical_attribute"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"clinical_attribute",
"isa",
"conceptual_entity"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"pharmacologic_substance",
"ingredient_of",
"clinical_drug"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"clinical_attribute"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
26, amino_acid_sequence
3, carbohydrate_sequence
24, daily_or_recreational_activity
42, geographic_area
70, idea_or_concept
36, machine_activity
32, molecular_sequence
134, nucleotide_sequence
83, organ_or_tissue_function
1, population_group
111, qualitative_concept
79, spatial_concept
108, temporal_concept
src, edge_attr, dst
26, isa, 70
26, isa, 32
26, isa, 79
3, isa, 70
3, isa, 32
3, isa, 79
42, isa, 70
42, isa, 79
32, isa, 70
32, isa, 79
134, isa, 70
134, isa, 32
134, isa, 79
83, conceptual_part_of, 108
83, occurs_in, 108
1, performs, 24
1, performs, 36
111, evaluation_of, 24
111, evaluation_of, 36
111, isa, 70
79, isa, 70
108, conceptual_part_of, 83
108, isa, 70
Question: For what reason are nucleotide_sequence, organ_or_tissue_function, and population_group associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"nucleotide_sequence",
"organ_or_tissue_function",
"population_group"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"organ_or_tissue_function",
"conceptual_part_of",
"temporal_concept"
],
[
"organ_or_tissue_function",
"occurs_in",
"temporal_concept"
],
[
"population_group",
"performs",
"daily_or_recreational_activity"
],
[
"population_group",
"performs",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"temporal_concept",
"conceptual_part_of",
"organ_or_tissue_function"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
33, eicosanoid
50, event
124, family_group
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
70, idea_or_concept
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
66, regulation_or_law
76, reptile
67, research_device
40, self_help_or_relief_organization
122, social_behavior
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
64, affects, 122
64, associated_with, 28
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
107, isa, 69
107, isa, 50
107, isa, 27
33, ingredient_of, 61
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
91, isa, 69
91, isa, 50
91, isa, 27
10, property_of, 28
10, property_of, 124
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
70, conceptual_part_of, 64
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
66, affects, 28
66, affects, 124
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
76, exhibits, 64
76, exhibits, 122
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
122, affects, 64
122, associated_with, 28
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: In what context are eicosanoid, occupational_activity, and reptile connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"eicosanoid",
"occupational_activity",
"reptile"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"eicosanoid",
"ingredient_of",
"clinical_drug"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"reptile",
"exhibits",
"behavior"
],
[
"reptile",
"exhibits",
"social_behavior"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
25, amphibian
64, behavior
17, conceptual_entity
107, educational_activity
42, geographic_area
10, group_attribute
70, idea_or_concept
125, nucleic_acid_nucleoside_or_nucleotide
134, nucleotide_sequence
111, qualitative_concept
122, social_behavior
src, edge_attr, dst
25, exhibits, 64
25, exhibits, 122
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, isa, 69
107, isa, 69
70, conceptual_part_of, 64
134, isa, 17
134, isa, 70
134, property_of, 125
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 107
111, evaluation_of, 122
111, isa, 17
111, isa, 70
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
Question: In what context are amphibian, educational_activity, and nucleic_acid_nucleoside_or_nucleotide connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amphibian",
"educational_activity",
"nucleic_acid_nucleoside_or_nucleotide"
],
"valid_edges": [
[
"amphibian",
"exhibits",
"behavior"
],
[
"amphibian",
"exhibits",
"social_behavior"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"activity"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"property_of",
"nucleic_acid_nucleoside_or_nucleotide"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
44, body_part_organ_or_organ_component
80, mental_or_behavioral_dysfunction
56, mental_process
src, edge_attr, dst
44, location_of, 80
44, location_of, 56
80, affects, 56
80, manifestation_of, 56
80, process_of, 56
80, result_of, 56
56, affects, 80
56, process_of, 80
56, result_of, 80
Question: In what context are body_part_organ_or_organ_component, mental_or_behavioral_dysfunction, and mental_process connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_part_organ_or_organ_component",
"mental_or_behavioral_dysfunction",
"mental_process"
],
"valid_edges": [
[
"body_part_organ_or_organ_component",
"location_of",
"mental_or_behavioral_dysfunction"
],
[
"body_part_organ_or_organ_component",
"location_of",
"mental_process"
],
[
"mental_or_behavioral_dysfunction",
"affects",
"mental_process"
],
[
"mental_or_behavioral_dysfunction",
"manifestation_of",
"mental_process"
],
[
"mental_or_behavioral_dysfunction",
"process_of",
"mental_process"
],
[
"mental_or_behavioral_dysfunction",
"result_of",
"mental_process"
],
[
"mental_process",
"affects",
"mental_or_behavioral_dysfunction"
],
[
"mental_process",
"process_of",
"mental_or_behavioral_dysfunction"
],
[
"mental_process",
"result_of",
"mental_or_behavioral_dysfunction"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
121, biomedical_or_dental_material
61, clinical_drug
50, event
124, family_group
42, geographic_area
10, group_attribute
37, mammal
111, qualitative_concept
76, reptile
122, social_behavior
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, performs, 64
28, performs, 122
28, produces, 61
28, uses, 61
64, affects, 122
64, associated_with, 28
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
121, ingredient_of, 61
124, exhibits, 64
124, exhibits, 122
124, performs, 64
124, performs, 122
124, produces, 61
124, uses, 61
37, exhibits, 64
37, exhibits, 122
111, evaluation_of, 64
111, evaluation_of, 122
76, exhibits, 64
76, exhibits, 122
76, interacts_with, 37
122, affects, 64
122, associated_with, 28
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: For what reason are biomedical_or_dental_material, mammal, and reptile associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biomedical_or_dental_material",
"mammal",
"reptile"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"biomedical_or_dental_material",
"ingredient_of",
"clinical_drug"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"mammal",
"exhibits",
"behavior"
],
[
"mammal",
"exhibits",
"social_behavior"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"reptile",
"exhibits",
"behavior"
],
[
"reptile",
"exhibits",
"social_behavior"
],
[
"reptile",
"interacts_with",
"mammal"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
22, anatomical_structure
73, archaeon
61, clinical_drug
68, drug_delivery_device
88, embryonic_structure
75, food
113, manufactured_object
125, nucleic_acid_nucleoside_or_nucleotide
126, physical_object
20, steroid
84, substance
src, edge_attr, dst
22, isa, 126
22, part_of, 73
73, isa, 126
61, isa, 113
61, isa, 126
68, contains, 61
68, isa, 126
88, isa, 22
88, isa, 126
88, part_of, 73
75, ingredient_of, 61
75, isa, 126
75, isa, 84
113, isa, 126
125, ingredient_of, 61
125, interacts_with, 20
125, isa, 126
125, isa, 84
20, ingredient_of, 61
20, isa, 126
20, isa, 84
84, ingredient_of, 61
84, isa, 126
Question: How are embryonic_structure, nucleic_acid_nucleoside_or_nucleotide, and steroid related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"embryonic_structure",
"nucleic_acid_nucleoside_or_nucleotide",
"steroid"
],
"valid_edges": [
[
"anatomical_structure",
"isa",
"physical_object"
],
[
"anatomical_structure",
"part_of",
"archaeon"
],
[
"archaeon",
"isa",
"physical_object"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"clinical_drug",
"isa",
"physical_object"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"physical_object"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"isa",
"physical_object"
],
[
"embryonic_structure",
"part_of",
"archaeon"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"physical_object"
],
[
"food",
"isa",
"substance"
],
[
"manufactured_object",
"isa",
"physical_object"
],
[
"nucleic_acid_nucleoside_or_nucleotide",
"ingredient_of",
"clinical_drug"
],
[
"nucleic_acid_nucleoside_or_nucleotide",
"interacts_with",
"steroid"
],
[
"nucleic_acid_nucleoside_or_nucleotide",
"isa",
"physical_object"
],
[
"nucleic_acid_nucleoside_or_nucleotide",
"isa",
"substance"
],
[
"steroid",
"ingredient_of",
"clinical_drug"
],
[
"steroid",
"isa",
"physical_object"
],
[
"steroid",
"isa",
"substance"
],
[
"substance",
"ingredient_of",
"clinical_drug"
],
[
"substance",
"isa",
"physical_object"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
124, family_group
75, food
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
13, indicator_reagent_or_diagnostic_aid
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
31, organization
41, professional_society
66, regulation_or_law
67, research_device
40, self_help_or_relief_organization
122, social_behavior
84, substance
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
64, associated_with, 28
64, associated_with, 124
48, isa, 17
48, isa, 55
61, isa, 113
68, contains, 61
68, isa, 113
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
75, ingredient_of, 61
75, isa, 84
10, isa, 17
10, property_of, 28
10, property_of, 124
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
13, ingredient_of, 61
13, isa, 84
55, isa, 17
59, isa, 113
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
66, affects, 28
66, affects, 124
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 17
66, isa, 55
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
122, associated_with, 28
122, associated_with, 124
84, ingredient_of, 61
Question: For what reason are classification, indicator_reagent_or_diagnostic_aid, and research_device associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"classification",
"indicator_reagent_or_diagnostic_aid",
"research_device"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"indicator_reagent_or_diagnostic_aid",
"ingredient_of",
"clinical_drug"
],
[
"indicator_reagent_or_diagnostic_aid",
"isa",
"substance"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"substance",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
62, disease_or_syndrome
52, laboratory_or_test_result
38, organic_chemical
src, edge_attr, dst
52, associated_with, 62
52, evaluation_of, 62
52, indicates, 62
52, manifestation_of, 62
52, measurement_of, 38
38, affects, 62
38, causes, 62
Question: For what reason are disease_or_syndrome, laboratory_or_test_result, and organic_chemical associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"disease_or_syndrome",
"laboratory_or_test_result",
"organic_chemical"
],
"valid_edges": [
[
"laboratory_or_test_result",
"associated_with",
"disease_or_syndrome"
],
[
"laboratory_or_test_result",
"evaluation_of",
"disease_or_syndrome"
],
[
"laboratory_or_test_result",
"indicates",
"disease_or_syndrome"
],
[
"laboratory_or_test_result",
"manifestation_of",
"disease_or_syndrome"
],
[
"laboratory_or_test_result",
"measurement_of",
"organic_chemical"
],
[
"organic_chemical",
"affects",
"disease_or_syndrome"
],
[
"organic_chemical",
"causes",
"disease_or_syndrome"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
17, conceptual_entity
52, laboratory_or_test_result
84, substance
src, edge_attr, dst
52, isa, 17
52, measurement_of, 84
Question: In what context are conceptual_entity, laboratory_or_test_result, and substance connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"conceptual_entity",
"laboratory_or_test_result",
"substance"
],
"valid_edges": [
[
"laboratory_or_test_result",
"isa",
"conceptual_entity"
],
[
"laboratory_or_test_result",
"measurement_of",
"substance"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
60, biologic_function
103, body_space_or_junction
53, health_care_activity
src, edge_attr, dst
103, location_of, 60
53, affects, 60
Question: In what context are biologic_function, body_space_or_junction, and health_care_activity connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biologic_function",
"body_space_or_junction",
"health_care_activity"
],
"valid_edges": [
[
"body_space_or_junction",
"location_of",
"biologic_function"
],
[
"health_care_activity",
"affects",
"biologic_function"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
22, anatomical_structure
73, archaeon
130, bacterium
64, behavior
6, chemical_viewed_structurally
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
88, embryonic_structure
124, family_group
75, food
91, governmental_or_regulatory_activity
16, group
10, group_attribute
53, health_care_activity
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
2, patient_or_disabled_group
126, physical_object
66, regulation_or_law
67, research_device
122, social_behavior
84, substance
src, edge_attr, dst
28, exhibits, 64
28, exhibits, 122
28, interacts_with, 16
28, interacts_with, 2
28, isa, 17
28, isa, 16
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
22, isa, 126
22, location_of, 130
22, part_of, 73
22, part_of, 130
73, isa, 126
130, interacts_with, 73
130, isa, 126
64, associated_with, 28
64, associated_with, 124
64, associated_with, 16
64, associated_with, 2
6, ingredient_of, 61
6, isa, 126
6, isa, 84
61, isa, 113
61, isa, 126
68, contains, 61
68, isa, 113
68, isa, 59
68, isa, 126
88, isa, 22
88, isa, 126
88, location_of, 130
88, part_of, 73
88, part_of, 130
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, interacts_with, 16
124, interacts_with, 2
124, isa, 17
124, isa, 16
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
75, ingredient_of, 61
75, isa, 126
75, isa, 84
16, exhibits, 64
16, exhibits, 122
16, isa, 17
16, performs, 69
16, performs, 64
16, performs, 24
16, performs, 107
16, performs, 91
16, performs, 53
16, performs, 36
16, performs, 27
16, performs, 122
16, produces, 48
16, produces, 61
16, produces, 68
16, produces, 55
16, produces, 113
16, produces, 59
16, produces, 66
16, produces, 67
16, uses, 48
16, uses, 61
16, uses, 68
16, uses, 55
16, uses, 113
16, uses, 59
16, uses, 66
16, uses, 67
10, property_of, 28
10, property_of, 124
10, property_of, 16
10, property_of, 2
113, isa, 126
59, isa, 113
59, isa, 126
2, exhibits, 64
2, exhibits, 122
2, interacts_with, 16
2, isa, 17
2, isa, 16
2, performs, 69
2, performs, 64
2, performs, 24
2, performs, 107
2, performs, 91
2, performs, 53
2, performs, 36
2, performs, 27
2, performs, 122
2, produces, 48
2, produces, 61
2, produces, 68
2, produces, 55
2, produces, 113
2, produces, 59
2, produces, 66
2, produces, 67
2, uses, 48
2, uses, 61
2, uses, 68
2, uses, 55
2, uses, 113
2, uses, 59
2, uses, 66
2, uses, 67
66, affects, 28
66, affects, 124
66, affects, 16
66, affects, 2
67, isa, 113
67, isa, 126
122, associated_with, 28
122, associated_with, 124
122, associated_with, 16
122, associated_with, 2
84, ingredient_of, 61
84, isa, 126
Question: In what context are bacterium, chemical_viewed_structurally, and clinical_drug connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bacterium",
"chemical_viewed_structurally",
"clinical_drug"
],
"valid_edges": [
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"interacts_with",
"group"
],
[
"age_group",
"interacts_with",
"patient_or_disabled_group"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"isa",
"group"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"anatomical_structure",
"isa",
"physical_object"
],
[
"anatomical_structure",
"location_of",
"bacterium"
],
[
"anatomical_structure",
"part_of",
"archaeon"
],
[
"anatomical_structure",
"part_of",
"bacterium"
],
[
"archaeon",
"isa",
"physical_object"
],
[
"bacterium",
"interacts_with",
"archaeon"
],
[
"bacterium",
"isa",
"physical_object"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"group"
],
[
"behavior",
"associated_with",
"patient_or_disabled_group"
],
[
"chemical_viewed_structurally",
"ingredient_of",
"clinical_drug"
],
[
"chemical_viewed_structurally",
"isa",
"physical_object"
],
[
"chemical_viewed_structurally",
"isa",
"substance"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"clinical_drug",
"isa",
"physical_object"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"drug_delivery_device",
"isa",
"physical_object"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"isa",
"physical_object"
],
[
"embryonic_structure",
"location_of",
"bacterium"
],
[
"embryonic_structure",
"part_of",
"archaeon"
],
[
"embryonic_structure",
"part_of",
"bacterium"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"interacts_with",
"group"
],
[
"family_group",
"interacts_with",
"patient_or_disabled_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"isa",
"group"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"physical_object"
],
[
"food",
"isa",
"substance"
],
[
"group",
"exhibits",
"behavior"
],
[
"group",
"exhibits",
"social_behavior"
],
[
"group",
"isa",
"conceptual_entity"
],
[
"group",
"performs",
"activity"
],
[
"group",
"performs",
"behavior"
],
[
"group",
"performs",
"daily_or_recreational_activity"
],
[
"group",
"performs",
"educational_activity"
],
[
"group",
"performs",
"governmental_or_regulatory_activity"
],
[
"group",
"performs",
"health_care_activity"
],
[
"group",
"performs",
"machine_activity"
],
[
"group",
"performs",
"occupational_activity"
],
[
"group",
"performs",
"social_behavior"
],
[
"group",
"produces",
"classification"
],
[
"group",
"produces",
"clinical_drug"
],
[
"group",
"produces",
"drug_delivery_device"
],
[
"group",
"produces",
"intellectual_product"
],
[
"group",
"produces",
"manufactured_object"
],
[
"group",
"produces",
"medical_device"
],
[
"group",
"produces",
"regulation_or_law"
],
[
"group",
"produces",
"research_device"
],
[
"group",
"uses",
"classification"
],
[
"group",
"uses",
"clinical_drug"
],
[
"group",
"uses",
"drug_delivery_device"
],
[
"group",
"uses",
"intellectual_product"
],
[
"group",
"uses",
"manufactured_object"
],
[
"group",
"uses",
"medical_device"
],
[
"group",
"uses",
"regulation_or_law"
],
[
"group",
"uses",
"research_device"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"group_attribute",
"property_of",
"group"
],
[
"group_attribute",
"property_of",
"patient_or_disabled_group"
],
[
"manufactured_object",
"isa",
"physical_object"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"medical_device",
"isa",
"physical_object"
],
[
"patient_or_disabled_group",
"exhibits",
"behavior"
],
[
"patient_or_disabled_group",
"exhibits",
"social_behavior"
],
[
"patient_or_disabled_group",
"interacts_with",
"group"
],
[
"patient_or_disabled_group",
"isa",
"conceptual_entity"
],
[
"patient_or_disabled_group",
"isa",
"group"
],
[
"patient_or_disabled_group",
"performs",
"activity"
],
[
"patient_or_disabled_group",
"performs",
"behavior"
],
[
"patient_or_disabled_group",
"performs",
"daily_or_recreational_activity"
],
[
"patient_or_disabled_group",
"performs",
"educational_activity"
],
[
"patient_or_disabled_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"patient_or_disabled_group",
"performs",
"health_care_activity"
],
[
"patient_or_disabled_group",
"performs",
"machine_activity"
],
[
"patient_or_disabled_group",
"performs",
"occupational_activity"
],
[
"patient_or_disabled_group",
"performs",
"social_behavior"
],
[
"patient_or_disabled_group",
"produces",
"classification"
],
[
"patient_or_disabled_group",
"produces",
"clinical_drug"
],
[
"patient_or_disabled_group",
"produces",
"drug_delivery_device"
],
[
"patient_or_disabled_group",
"produces",
"intellectual_product"
],
[
"patient_or_disabled_group",
"produces",
"manufactured_object"
],
[
"patient_or_disabled_group",
"produces",
"medical_device"
],
[
"patient_or_disabled_group",
"produces",
"regulation_or_law"
],
[
"patient_or_disabled_group",
"produces",
"research_device"
],
[
"patient_or_disabled_group",
"uses",
"classification"
],
[
"patient_or_disabled_group",
"uses",
"clinical_drug"
],
[
"patient_or_disabled_group",
"uses",
"drug_delivery_device"
],
[
"patient_or_disabled_group",
"uses",
"intellectual_product"
],
[
"patient_or_disabled_group",
"uses",
"manufactured_object"
],
[
"patient_or_disabled_group",
"uses",
"medical_device"
],
[
"patient_or_disabled_group",
"uses",
"regulation_or_law"
],
[
"patient_or_disabled_group",
"uses",
"research_device"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"affects",
"group"
],
[
"regulation_or_law",
"affects",
"patient_or_disabled_group"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"research_device",
"isa",
"physical_object"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"group"
],
[
"social_behavior",
"associated_with",
"patient_or_disabled_group"
],
[
"substance",
"ingredient_of",
"clinical_drug"
],
[
"substance",
"isa",
"physical_object"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
81, element_ion_or_isotope
83, organ_or_tissue_function
39, research_activity
src, edge_attr, dst
81, affects, 83
39, measures, 81
39, measures, 83
Question: For what reason are element_ion_or_isotope, organ_or_tissue_function, and research_activity associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"element_ion_or_isotope",
"organ_or_tissue_function",
"research_activity"
],
"valid_edges": [
[
"element_ion_or_isotope",
"affects",
"organ_or_tissue_function"
],
[
"research_activity",
"measures",
"element_ion_or_isotope"
],
[
"research_activity",
"measures",
"organ_or_tissue_function"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
132, body_system
62, disease_or_syndrome
42, geographic_area
70, idea_or_concept
18, physiologic_function
79, spatial_concept
src, edge_attr, dst
132, isa, 70
62, affects, 18
62, manifestation_of, 18
62, process_of, 18
62, result_of, 18
42, associated_with, 62
42, isa, 70
42, isa, 79
18, affects, 62
18, process_of, 62
18, result_of, 62
79, isa, 70
Question: For what reason are body_system, disease_or_syndrome, and physiologic_function associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_system",
"disease_or_syndrome",
"physiologic_function"
],
"valid_edges": [
[
"body_system",
"isa",
"idea_or_concept"
],
[
"disease_or_syndrome",
"affects",
"physiologic_function"
],
[
"disease_or_syndrome",
"manifestation_of",
"physiologic_function"
],
[
"disease_or_syndrome",
"process_of",
"physiologic_function"
],
[
"disease_or_syndrome",
"result_of",
"physiologic_function"
],
[
"geographic_area",
"associated_with",
"disease_or_syndrome"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"physiologic_function",
"affects",
"disease_or_syndrome"
],
[
"physiologic_function",
"process_of",
"disease_or_syndrome"
],
[
"physiologic_function",
"result_of",
"disease_or_syndrome"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
62, disease_or_syndrome
104, fish
119, organism
src, edge_attr, dst
62, affects, 104
62, affects, 119
62, process_of, 104
62, process_of, 119
104, interacts_with, 119
104, isa, 119
Question: How are disease_or_syndrome, fish, and organism related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"disease_or_syndrome",
"fish",
"organism"
],
"valid_edges": [
[
"disease_or_syndrome",
"affects",
"fish"
],
[
"disease_or_syndrome",
"affects",
"organism"
],
[
"disease_or_syndrome",
"process_of",
"fish"
],
[
"disease_or_syndrome",
"process_of",
"organism"
],
[
"fish",
"interacts_with",
"organism"
],
[
"fish",
"isa",
"organism"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
123, diagnostic_procedure
58, occupation_or_discipline
111, qualitative_concept
src, edge_attr, dst
123, issue_in, 58
123, method_of, 58
111, evaluation_of, 123
111, issue_in, 58
Question: In what context are diagnostic_procedure, occupation_or_discipline, and qualitative_concept connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"diagnostic_procedure",
"occupation_or_discipline",
"qualitative_concept"
],
"valid_edges": [
[
"diagnostic_procedure",
"issue_in",
"occupation_or_discipline"
],
[
"diagnostic_procedure",
"method_of",
"occupation_or_discipline"
],
[
"qualitative_concept",
"evaluation_of",
"diagnostic_procedure"
],
[
"qualitative_concept",
"issue_in",
"occupation_or_discipline"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
112, alga
97, injury_or_poisoning
83, organ_or_tissue_function
src, edge_attr, dst
97, disrupts, 83
97, result_of, 83
83, affects, 112
83, process_of, 112
83, result_of, 97
Question: In what context are alga, injury_or_poisoning, and organ_or_tissue_function connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"alga",
"injury_or_poisoning",
"organ_or_tissue_function"
],
"valid_edges": [
[
"injury_or_poisoning",
"disrupts",
"organ_or_tissue_function"
],
[
"injury_or_poisoning",
"result_of",
"organ_or_tissue_function"
],
[
"organ_or_tissue_function",
"affects",
"alga"
],
[
"organ_or_tissue_function",
"process_of",
"alga"
],
[
"organ_or_tissue_function",
"result_of",
"injury_or_poisoning"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
121, biomedical_or_dental_material
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
50, event
124, family_group
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
70, idea_or_concept
55, intellectual_product
30, language
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
111, qualitative_concept
66, regulation_or_law
67, research_device
122, social_behavior
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
64, associated_with, 28
64, associated_with, 124
64, isa, 69
64, isa, 50
121, ingredient_of, 61
48, isa, 17
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
107, isa, 69
107, isa, 50
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
91, isa, 69
91, isa, 50
10, isa, 17
10, property_of, 28
10, property_of, 124
53, isa, 69
53, isa, 50
70, isa, 17
55, isa, 17
30, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
66, affects, 28
66, affects, 124
66, isa, 17
122, associated_with, 28
122, associated_with, 124
122, isa, 69
122, isa, 50
Question: How are biomedical_or_dental_material, language, and machine_activity related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biomedical_or_dental_material",
"language",
"machine_activity"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"biomedical_or_dental_material",
"ingredient_of",
"clinical_drug"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"language",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
15, cell_function
61, clinical_drug
75, food
109, genetic_function
70, idea_or_concept
96, quantitative_concept
108, temporal_concept
src, edge_attr, dst
15, affects, 109
15, co-occurs_with, 109
15, occurs_in, 108
15, precedes, 109
15, process_of, 109
15, result_of, 109
75, affects, 15
75, affects, 109
75, ingredient_of, 61
109, affects, 15
109, occurs_in, 108
109, precedes, 15
109, process_of, 15
109, result_of, 15
96, isa, 70
96, measurement_of, 15
96, measurement_of, 109
108, conceptual_part_of, 15
108, isa, 70
Question: In what context are cell_function, clinical_drug, and genetic_function connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"cell_function",
"clinical_drug",
"genetic_function"
],
"valid_edges": [
[
"cell_function",
"affects",
"genetic_function"
],
[
"cell_function",
"co-occurs_with",
"genetic_function"
],
[
"cell_function",
"occurs_in",
"temporal_concept"
],
[
"cell_function",
"precedes",
"genetic_function"
],
[
"cell_function",
"process_of",
"genetic_function"
],
[
"cell_function",
"result_of",
"genetic_function"
],
[
"food",
"affects",
"cell_function"
],
[
"food",
"affects",
"genetic_function"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"genetic_function",
"affects",
"cell_function"
],
[
"genetic_function",
"occurs_in",
"temporal_concept"
],
[
"genetic_function",
"precedes",
"cell_function"
],
[
"genetic_function",
"process_of",
"cell_function"
],
[
"genetic_function",
"result_of",
"cell_function"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"cell_function"
],
[
"quantitative_concept",
"measurement_of",
"genetic_function"
],
[
"temporal_concept",
"conceptual_part_of",
"cell_function"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
60, biologic_function
48, classification
24, daily_or_recreational_activity
70, idea_or_concept
55, intellectual_product
36, machine_activity
41, professional_society
111, qualitative_concept
96, quantitative_concept
7, therapeutic_or_preventive_procedure
src, edge_attr, dst
48, isa, 55
24, isa, 69
36, isa, 69
36, method_of, 7
41, carries_out, 7
41, location_of, 7
41, produces, 48
41, produces, 55
111, evaluation_of, 69
111, evaluation_of, 24
111, evaluation_of, 36
111, evaluation_of, 7
111, isa, 70
96, conceptual_part_of, 7
96, isa, 70
7, affects, 60
7, complicates, 60
7, isa, 69
Question: How are biologic_function, intellectual_product, and therapeutic_or_preventive_procedure related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biologic_function",
"intellectual_product",
"therapeutic_or_preventive_procedure"
],
"valid_edges": [
[
"classification",
"isa",
"intellectual_product"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"method_of",
"therapeutic_or_preventive_procedure"
],
[
"professional_society",
"carries_out",
"therapeutic_or_preventive_procedure"
],
[
"professional_society",
"location_of",
"therapeutic_or_preventive_procedure"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"therapeutic_or_preventive_procedure"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"conceptual_part_of",
"therapeutic_or_preventive_procedure"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"therapeutic_or_preventive_procedure",
"affects",
"biologic_function"
],
[
"therapeutic_or_preventive_procedure",
"complicates",
"biologic_function"
],
[
"therapeutic_or_preventive_procedure",
"isa",
"activity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
65, biomedical_occupation_or_discipline
72, pharmacologic_substance
96, quantitative_concept
src, edge_attr, dst
72, issue_in, 65
96, issue_in, 65
Question: For what reason are biomedical_occupation_or_discipline, pharmacologic_substance, and quantitative_concept associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biomedical_occupation_or_discipline",
"pharmacologic_substance",
"quantitative_concept"
],
"valid_edges": [
[
"pharmacologic_substance",
"issue_in",
"biomedical_occupation_or_discipline"
],
[
"quantitative_concept",
"issue_in",
"biomedical_occupation_or_discipline"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
26, amino_acid_sequence
29, neoplastic_process
58, occupation_or_discipline
src, edge_attr, dst
26, issue_in, 58
29, issue_in, 58
Question: How are amino_acid_sequence, neoplastic_process, and occupation_or_discipline related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_sequence",
"neoplastic_process",
"occupation_or_discipline"
],
"valid_edges": [
[
"amino_acid_sequence",
"issue_in",
"occupation_or_discipline"
],
[
"neoplastic_process",
"issue_in",
"occupation_or_discipline"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
129, body_substance
62, disease_or_syndrome
87, plant
src, edge_attr, dst
129, causes, 62
62, affects, 87
62, process_of, 87
62, produces, 129
Question: In what context are body_substance, disease_or_syndrome, and plant connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_substance",
"disease_or_syndrome",
"plant"
],
"valid_edges": [
[
"body_substance",
"causes",
"disease_or_syndrome"
],
[
"disease_or_syndrome",
"affects",
"plant"
],
[
"disease_or_syndrome",
"process_of",
"plant"
],
[
"disease_or_syndrome",
"produces",
"body_substance"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
112, alga
94, body_location_or_region
103, body_space_or_junction
129, body_substance
132, body_system
61, clinical_drug
17, conceptual_entity
88, embryonic_structure
75, food
16, group
70, idea_or_concept
84, substance
src, edge_attr, dst
94, adjacent_to, 103
94, conceptual_part_of, 132
94, isa, 17
103, conceptual_part_of, 132
103, contains, 129
103, isa, 17
103, isa, 70
103, location_of, 129
129, conceptual_part_of, 132
129, ingredient_of, 61
129, isa, 84
129, surrounds, 88
132, isa, 17
132, isa, 70
88, contains, 129
88, part_of, 112
75, ingredient_of, 61
75, isa, 84
16, isa, 17
16, produces, 61
16, uses, 61
70, isa, 17
84, ingredient_of, 61
Question: For what reason are alga, body_substance, and group associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"alga",
"body_substance",
"group"
],
"valid_edges": [
[
"body_location_or_region",
"adjacent_to",
"body_space_or_junction"
],
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"contains",
"body_substance"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"location_of",
"body_substance"
],
[
"body_substance",
"conceptual_part_of",
"body_system"
],
[
"body_substance",
"ingredient_of",
"clinical_drug"
],
[
"body_substance",
"isa",
"substance"
],
[
"body_substance",
"surrounds",
"embryonic_structure"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"embryonic_structure",
"contains",
"body_substance"
],
[
"embryonic_structure",
"part_of",
"alga"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"group",
"isa",
"conceptual_entity"
],
[
"group",
"produces",
"clinical_drug"
],
[
"group",
"uses",
"clinical_drug"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"substance",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
50, event
124, family_group
75, food
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
70, idea_or_concept
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
111, qualitative_concept
117, receptor
66, regulation_or_law
67, research_device
122, social_behavior
84, substance
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
64, affects, 122
64, associated_with, 28
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
48, isa, 17
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
107, isa, 69
107, isa, 50
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
75, ingredient_of, 61
75, isa, 84
42, isa, 17
91, isa, 69
91, isa, 50
10, isa, 17
10, property_of, 28
10, property_of, 124
53, isa, 69
53, isa, 50
70, conceptual_part_of, 64
70, isa, 17
55, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
117, ingredient_of, 61
117, isa, 84
66, affects, 28
66, affects, 124
66, isa, 17
122, affects, 64
122, associated_with, 28
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
84, ingredient_of, 61
Question: How are group_attribute, machine_activity, and receptor related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"group_attribute",
"machine_activity",
"receptor"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"receptor",
"ingredient_of",
"clinical_drug"
],
[
"receptor",
"isa",
"substance"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"substance",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
28, age_group
22, anatomical_structure
130, bacterium
61, clinical_drug
17, conceptual_entity
68, drug_delivery_device
88, embryonic_structure
124, family_group
75, food
82, functional_concept
42, geographic_area
70, idea_or_concept
113, manufactured_object
59, medical_device
126, physical_object
111, qualitative_concept
67, research_device
84, substance
src, edge_attr, dst
28, isa, 17
28, produces, 61
28, produces, 68
28, produces, 113
28, produces, 59
28, produces, 67
28, uses, 61
28, uses, 68
28, uses, 113
28, uses, 59
28, uses, 67
22, isa, 126
22, location_of, 130
22, part_of, 130
130, isa, 126
61, isa, 113
61, isa, 126
68, contains, 61
68, isa, 113
68, isa, 59
68, isa, 126
88, isa, 22
88, isa, 126
88, location_of, 130
88, part_of, 130
124, isa, 17
124, produces, 61
124, produces, 68
124, produces, 113
124, produces, 59
124, produces, 67
124, uses, 61
124, uses, 68
124, uses, 113
124, uses, 59
124, uses, 67
75, ingredient_of, 61
75, isa, 126
75, isa, 84
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
70, isa, 17
113, isa, 126
59, isa, 113
59, isa, 126
111, isa, 17
111, isa, 70
67, isa, 113
67, isa, 126
84, ingredient_of, 61
84, isa, 126
Question: In what context are bacterium, functional_concept, and physical_object connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bacterium",
"functional_concept",
"physical_object"
],
"valid_edges": [
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"research_device"
],
[
"anatomical_structure",
"isa",
"physical_object"
],
[
"anatomical_structure",
"location_of",
"bacterium"
],
[
"anatomical_structure",
"part_of",
"bacterium"
],
[
"bacterium",
"isa",
"physical_object"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"clinical_drug",
"isa",
"physical_object"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"drug_delivery_device",
"isa",
"physical_object"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"isa",
"physical_object"
],
[
"embryonic_structure",
"location_of",
"bacterium"
],
[
"embryonic_structure",
"part_of",
"bacterium"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"research_device"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"physical_object"
],
[
"food",
"isa",
"substance"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"manufactured_object",
"isa",
"physical_object"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"medical_device",
"isa",
"physical_object"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"research_device",
"isa",
"physical_object"
],
[
"substance",
"ingredient_of",
"clinical_drug"
],
[
"substance",
"isa",
"physical_object"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
86, experimental_model_of_disease
35, gene_or_genome
59, medical_device
src, edge_attr, dst
35, location_of, 86
59, causes, 86
59, prevents, 86
59, treats, 86
Question: How are experimental_model_of_disease, gene_or_genome, and medical_device related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"experimental_model_of_disease",
"gene_or_genome",
"medical_device"
],
"valid_edges": [
[
"gene_or_genome",
"location_of",
"experimental_model_of_disease"
],
[
"medical_device",
"causes",
"experimental_model_of_disease"
],
[
"medical_device",
"prevents",
"experimental_model_of_disease"
],
[
"medical_device",
"treats",
"experimental_model_of_disease"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
121, biomedical_or_dental_material
92, cell
110, molecular_function
src, edge_attr, dst
121, affects, 110
92, location_of, 110
Question: In what context are biomedical_or_dental_material, cell, and molecular_function connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biomedical_or_dental_material",
"cell",
"molecular_function"
],
"valid_edges": [
[
"biomedical_or_dental_material",
"affects",
"molecular_function"
],
[
"cell",
"location_of",
"molecular_function"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
24, daily_or_recreational_activity
42, geographic_area
45, human_caused_phenomenon_or_process
70, idea_or_concept
36, machine_activity
98, pathologic_function
111, qualitative_concept
src, edge_attr, dst
24, associated_with, 98
24, isa, 69
42, associated_with, 98
42, isa, 70
45, result_of, 98
36, isa, 69
98, result_of, 45
111, evaluation_of, 69
111, evaluation_of, 24
111, evaluation_of, 36
111, isa, 70
Question: How are activity, human_caused_phenomenon_or_process, and pathologic_function related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"activity",
"human_caused_phenomenon_or_process",
"pathologic_function"
],
"valid_edges": [
[
"daily_or_recreational_activity",
"associated_with",
"pathologic_function"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"geographic_area",
"associated_with",
"pathologic_function"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"human_caused_phenomenon_or_process",
"result_of",
"pathologic_function"
],
[
"machine_activity",
"isa",
"activity"
],
[
"pathologic_function",
"result_of",
"human_caused_phenomenon_or_process"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
130, bacterium
132, body_system
133, fully_formed_anatomical_structure
82, functional_concept
70, idea_or_concept
96, quantitative_concept
src, edge_attr, dst
132, conceptual_part_of, 133
132, isa, 82
132, isa, 70
133, location_of, 130
133, part_of, 130
82, isa, 70
96, isa, 70
Question: How are bacterium, fully_formed_anatomical_structure, and quantitative_concept related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bacterium",
"fully_formed_anatomical_structure",
"quantitative_concept"
],
"valid_edges": [
[
"body_system",
"conceptual_part_of",
"fully_formed_anatomical_structure"
],
[
"body_system",
"isa",
"functional_concept"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"fully_formed_anatomical_structure",
"location_of",
"bacterium"
],
[
"fully_formed_anatomical_structure",
"part_of",
"bacterium"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
80, mental_or_behavioral_dysfunction
98, pathologic_function
67, research_device
src, edge_attr, dst
80, affects, 98
80, associated_with, 98
80, co-occurs_with, 98
80, complicates, 98
80, degree_of, 98
80, isa, 98
80, manifestation_of, 98
80, precedes, 98
80, process_of, 98
80, result_of, 98
98, affects, 80
98, complicates, 80
98, degree_of, 80
98, manifestation_of, 80
98, occurs_in, 80
98, precedes, 80
98, process_of, 80
98, result_of, 80
67, causes, 80
67, causes, 98
Question: In what context are mental_or_behavioral_dysfunction, pathologic_function, and research_device connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"mental_or_behavioral_dysfunction",
"pathologic_function",
"research_device"
],
"valid_edges": [
[
"mental_or_behavioral_dysfunction",
"affects",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"associated_with",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"co-occurs_with",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"complicates",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"degree_of",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"isa",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"manifestation_of",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"precedes",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"process_of",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"result_of",
"pathologic_function"
],
[
"pathologic_function",
"affects",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"complicates",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"degree_of",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"manifestation_of",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"occurs_in",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"precedes",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"process_of",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"result_of",
"mental_or_behavioral_dysfunction"
],
[
"research_device",
"causes",
"mental_or_behavioral_dysfunction"
],
[
"research_device",
"causes",
"pathologic_function"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
15, cell_function
37, mammal
72, pharmacologic_substance
src, edge_attr, dst
15, affects, 37
15, process_of, 37
72, affects, 15
72, complicates, 15
72, disrupts, 15
Question: In what context are cell_function, mammal, and pharmacologic_substance connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"cell_function",
"mammal",
"pharmacologic_substance"
],
"valid_edges": [
[
"cell_function",
"affects",
"mammal"
],
[
"cell_function",
"process_of",
"mammal"
],
[
"pharmacologic_substance",
"affects",
"cell_function"
],
[
"pharmacologic_substance",
"complicates",
"cell_function"
],
[
"pharmacologic_substance",
"disrupts",
"cell_function"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
28, age_group
64, behavior
6, chemical_viewed_structurally
61, clinical_drug
17, conceptual_entity
124, family_group
42, geographic_area
70, idea_or_concept
134, nucleotide_sequence
111, qualitative_concept
96, quantitative_concept
src, edge_attr, dst
28, isa, 17
28, produces, 61
28, uses, 61
64, associated_with, 42
6, ingredient_of, 61
124, isa, 17
124, produces, 61
124, uses, 61
42, isa, 17
42, isa, 70
70, conceptual_part_of, 64
70, isa, 17
134, isa, 17
134, isa, 70
111, isa, 17
111, isa, 70
96, isa, 17
96, isa, 70
96, measurement_of, 42
96, measurement_of, 134
Question: In what context are chemical_viewed_structurally, nucleotide_sequence, and quantitative_concept connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"chemical_viewed_structurally",
"nucleotide_sequence",
"quantitative_concept"
],
"valid_edges": [
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"chemical_viewed_structurally",
"ingredient_of",
"clinical_drug"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"quantitative_concept",
"measurement_of",
"nucleotide_sequence"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
22, anatomical_structure
90, antibiotic
64, behavior
88, embryonic_structure
114, vertebrate
src, edge_attr, dst
22, part_of, 114
90, disrupts, 88
88, isa, 22
88, part_of, 114
114, exhibits, 64
Question: For what reason are antibiotic, behavior, and vertebrate associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"antibiotic",
"behavior",
"vertebrate"
],
"valid_edges": [
[
"anatomical_structure",
"part_of",
"vertebrate"
],
[
"antibiotic",
"disrupts",
"embryonic_structure"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"part_of",
"vertebrate"
],
[
"vertebrate",
"exhibits",
"behavior"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
12, individual_behavior
80, mental_or_behavioral_dysfunction
98, pathologic_function
src, edge_attr, dst
12, associated_with, 80
12, associated_with, 98
12, manifestation_of, 80
80, affects, 12
80, affects, 98
80, associated_with, 98
80, co-occurs_with, 98
80, complicates, 98
80, degree_of, 98
80, isa, 98
80, manifestation_of, 98
80, precedes, 98
80, process_of, 98
80, result_of, 12
80, result_of, 98
98, affects, 80
98, complicates, 80
98, degree_of, 80
98, manifestation_of, 80
98, occurs_in, 80
98, precedes, 80
98, process_of, 80
98, result_of, 12
98, result_of, 80
Question: For what reason are individual_behavior, mental_or_behavioral_dysfunction, and pathologic_function associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"individual_behavior",
"mental_or_behavioral_dysfunction",
"pathologic_function"
],
"valid_edges": [
[
"individual_behavior",
"associated_with",
"mental_or_behavioral_dysfunction"
],
[
"individual_behavior",
"associated_with",
"pathologic_function"
],
[
"individual_behavior",
"manifestation_of",
"mental_or_behavioral_dysfunction"
],
[
"mental_or_behavioral_dysfunction",
"affects",
"individual_behavior"
],
[
"mental_or_behavioral_dysfunction",
"affects",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"associated_with",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"co-occurs_with",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"complicates",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"degree_of",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"isa",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"manifestation_of",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"precedes",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"process_of",
"pathologic_function"
],
[
"mental_or_behavioral_dysfunction",
"result_of",
"individual_behavior"
],
[
"mental_or_behavioral_dysfunction",
"result_of",
"pathologic_function"
],
[
"pathologic_function",
"affects",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"complicates",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"degree_of",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"manifestation_of",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"occurs_in",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"precedes",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"process_of",
"mental_or_behavioral_dysfunction"
],
[
"pathologic_function",
"result_of",
"individual_behavior"
],
[
"pathologic_function",
"result_of",
"mental_or_behavioral_dysfunction"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
57, amino_acid_peptide_or_protein
26, amino_acid_sequence
24, daily_or_recreational_activity
70, idea_or_concept
36, machine_activity
2, patient_or_disabled_group
111, qualitative_concept
7, therapeutic_or_preventive_procedure
src, edge_attr, dst
26, isa, 70
26, property_of, 57
36, method_of, 7
2, performs, 24
2, performs, 36
2, performs, 7
111, evaluation_of, 24
111, evaluation_of, 36
111, evaluation_of, 7
111, isa, 70
7, affects, 2
Question: For what reason are amino_acid_peptide_or_protein, patient_or_disabled_group, and therapeutic_or_preventive_procedure associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_peptide_or_protein",
"patient_or_disabled_group",
"therapeutic_or_preventive_procedure"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"property_of",
"amino_acid_peptide_or_protein"
],
[
"machine_activity",
"method_of",
"therapeutic_or_preventive_procedure"
],
[
"patient_or_disabled_group",
"performs",
"daily_or_recreational_activity"
],
[
"patient_or_disabled_group",
"performs",
"machine_activity"
],
[
"patient_or_disabled_group",
"performs",
"therapeutic_or_preventive_procedure"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"therapeutic_or_preventive_procedure"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"therapeutic_or_preventive_procedure",
"affects",
"patient_or_disabled_group"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
26, amino_acid_sequence
64, behavior
94, body_location_or_region
103, body_space_or_junction
132, body_system
3, carbohydrate_sequence
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
50, event
104, fish
82, functional_concept
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
70, idea_or_concept
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
32, molecular_sequence
134, nucleotide_sequence
27, occupational_activity
31, organization
23, professional_or_occupational_group
41, professional_society
111, qualitative_concept
96, quantitative_concept
66, regulation_or_law
67, research_device
40, self_help_or_relief_organization
122, social_behavior
79, spatial_concept
108, temporal_concept
src, edge_attr, dst
69, isa, 50
26, isa, 17
26, isa, 70
26, isa, 32
26, isa, 79
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, associated_with, 23
64, isa, 69
64, isa, 50
94, isa, 17
94, isa, 70
94, isa, 79
103, isa, 17
103, isa, 70
103, isa, 79
132, isa, 17
132, isa, 70
3, isa, 17
3, isa, 70
3, isa, 32
3, isa, 79
48, isa, 17
48, isa, 55
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
68, isa, 113
68, isa, 59
107, isa, 69
107, isa, 50
107, isa, 27
104, exhibits, 64
104, exhibits, 122
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
42, isa, 79
91, isa, 69
91, isa, 50
91, isa, 27
10, isa, 17
10, property_of, 23
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, isa, 31
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
128, produces, 48
128, produces, 55
128, produces, 66
70, conceptual_part_of, 64
70, isa, 17
55, isa, 17
36, isa, 69
36, isa, 50
59, isa, 113
32, isa, 17
32, isa, 70
32, isa, 79
134, isa, 17
134, isa, 70
134, isa, 32
134, isa, 79
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
31, produces, 48
31, produces, 55
31, produces, 66
23, exhibits, 64
23, exhibits, 122
23, isa, 17
23, manages, 128
23, manages, 31
23, manages, 41
23, manages, 40
23, performs, 69
23, performs, 64
23, performs, 24
23, performs, 107
23, performs, 91
23, performs, 53
23, performs, 36
23, performs, 27
23, performs, 122
23, produces, 48
23, produces, 61
23, produces, 68
23, produces, 55
23, produces, 113
23, produces, 59
23, produces, 66
23, produces, 67
23, uses, 48
23, uses, 61
23, uses, 68
23, uses, 55
23, uses, 113
23, uses, 59
23, uses, 66
23, uses, 67
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, isa, 31
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
96, isa, 17
96, isa, 70
96, measurement_of, 26
96, measurement_of, 94
96, measurement_of, 103
96, measurement_of, 3
96, measurement_of, 42
96, measurement_of, 32
96, measurement_of, 134
96, measurement_of, 79
66, affects, 128
66, affects, 31
66, affects, 23
66, affects, 41
66, affects, 40
66, isa, 17
66, isa, 55
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, isa, 31
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
40, produces, 48
40, produces, 55
40, produces, 66
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, associated_with, 23
122, isa, 69
122, isa, 64
122, isa, 50
79, isa, 17
79, isa, 70
108, isa, 17
108, isa, 70
Question: In what context are amino_acid_sequence, fish, and professional_or_occupational_group connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_sequence",
"fish",
"professional_or_occupational_group"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"amino_acid_sequence",
"isa",
"conceptual_entity"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"associated_with",
"professional_or_occupational_group"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"isa",
"spatial_concept"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"conceptual_entity"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"fish",
"exhibits",
"behavior"
],
[
"fish",
"exhibits",
"social_behavior"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"professional_or_occupational_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"molecular_sequence",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_or_occupational_group",
"exhibits",
"behavior"
],
[
"professional_or_occupational_group",
"exhibits",
"social_behavior"
],
[
"professional_or_occupational_group",
"isa",
"conceptual_entity"
],
[
"professional_or_occupational_group",
"manages",
"health_care_related_organization"
],
[
"professional_or_occupational_group",
"manages",
"organization"
],
[
"professional_or_occupational_group",
"manages",
"professional_society"
],
[
"professional_or_occupational_group",
"manages",
"self_help_or_relief_organization"
],
[
"professional_or_occupational_group",
"performs",
"activity"
],
[
"professional_or_occupational_group",
"performs",
"behavior"
],
[
"professional_or_occupational_group",
"performs",
"daily_or_recreational_activity"
],
[
"professional_or_occupational_group",
"performs",
"educational_activity"
],
[
"professional_or_occupational_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"professional_or_occupational_group",
"performs",
"health_care_activity"
],
[
"professional_or_occupational_group",
"performs",
"machine_activity"
],
[
"professional_or_occupational_group",
"performs",
"occupational_activity"
],
[
"professional_or_occupational_group",
"performs",
"social_behavior"
],
[
"professional_or_occupational_group",
"produces",
"classification"
],
[
"professional_or_occupational_group",
"produces",
"clinical_drug"
],
[
"professional_or_occupational_group",
"produces",
"drug_delivery_device"
],
[
"professional_or_occupational_group",
"produces",
"intellectual_product"
],
[
"professional_or_occupational_group",
"produces",
"manufactured_object"
],
[
"professional_or_occupational_group",
"produces",
"medical_device"
],
[
"professional_or_occupational_group",
"produces",
"regulation_or_law"
],
[
"professional_or_occupational_group",
"produces",
"research_device"
],
[
"professional_or_occupational_group",
"uses",
"classification"
],
[
"professional_or_occupational_group",
"uses",
"clinical_drug"
],
[
"professional_or_occupational_group",
"uses",
"drug_delivery_device"
],
[
"professional_or_occupational_group",
"uses",
"intellectual_product"
],
[
"professional_or_occupational_group",
"uses",
"manufactured_object"
],
[
"professional_or_occupational_group",
"uses",
"medical_device"
],
[
"professional_or_occupational_group",
"uses",
"regulation_or_law"
],
[
"professional_or_occupational_group",
"uses",
"research_device"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"amino_acid_sequence"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"body_space_or_junction"
],
[
"quantitative_concept",
"measurement_of",
"carbohydrate_sequence"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"quantitative_concept",
"measurement_of",
"molecular_sequence"
],
[
"quantitative_concept",
"measurement_of",
"nucleotide_sequence"
],
[
"quantitative_concept",
"measurement_of",
"spatial_concept"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_or_occupational_group"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"associated_with",
"professional_or_occupational_group"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"spatial_concept",
"isa",
"conceptual_entity"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"temporal_concept",
"isa",
"conceptual_entity"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
22, anatomical_structure
94, body_location_or_region
103, body_space_or_junction
132, body_system
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
88, embryonic_structure
43, environmental_effect_of_humans
50, event
89, finding
75, food
42, geographic_area
91, governmental_or_regulatory_activity
128, health_care_related_organization
45, human_caused_phenomenon_or_process
70, idea_or_concept
97, injury_or_poisoning
14, inorganic_chemical
37, mammal
113, manufactured_object
59, medical_device
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
96, quantitative_concept
67, research_device
40, self_help_or_relief_organization
79, spatial_concept
84, substance
src, edge_attr, dst
69, isa, 50
22, part_of, 37
94, adjacent_to, 103
94, conceptual_part_of, 132
94, isa, 17
94, isa, 70
94, isa, 79
94, location_of, 97
103, conceptual_part_of, 132
103, isa, 17
103, isa, 70
103, isa, 79
103, location_of, 97
61, causes, 97
61, isa, 113
24, associated_with, 97
24, isa, 69
24, isa, 50
68, causes, 97
68, contains, 61
68, isa, 113
68, isa, 59
68, prevents, 97
68, treats, 97
107, associated_with, 97
107, isa, 69
107, isa, 50
107, isa, 27
88, isa, 22
88, part_of, 37
43, isa, 50
43, isa, 45
43, result_of, 45
43, result_of, 97
89, associated_with, 97
89, isa, 17
89, manifestation_of, 97
75, causes, 97
75, ingredient_of, 61
75, isa, 84
42, associated_with, 97
42, isa, 17
42, isa, 70
42, isa, 79
91, associated_with, 97
91, isa, 69
91, isa, 50
91, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 27
128, location_of, 107
128, location_of, 91
128, location_of, 27
45, isa, 50
45, result_of, 43
45, result_of, 97
97, disrupts, 88
97, isa, 50
97, result_of, 43
97, result_of, 45
14, causes, 97
14, ingredient_of, 61
14, isa, 84
113, causes, 97
59, causes, 97
59, isa, 113
59, prevents, 97
59, treats, 97
27, associated_with, 97
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 27
31, location_of, 107
31, location_of, 91
31, location_of, 27
41, carries_out, 107
41, carries_out, 91
41, carries_out, 27
41, location_of, 107
41, location_of, 91
41, location_of, 27
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 27
96, measurement_of, 94
96, measurement_of, 103
96, measurement_of, 42
67, causes, 97
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, carries_out, 27
40, location_of, 107
40, location_of, 91
40, location_of, 27
84, causes, 97
84, ingredient_of, 61
Question: In what context are injury_or_poisoning, inorganic_chemical, and mammal connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"injury_or_poisoning",
"inorganic_chemical",
"mammal"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"anatomical_structure",
"part_of",
"mammal"
],
[
"body_location_or_region",
"adjacent_to",
"body_space_or_junction"
],
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_location_or_region",
"location_of",
"injury_or_poisoning"
],
[
"body_space_or_junction",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"isa",
"spatial_concept"
],
[
"body_space_or_junction",
"location_of",
"injury_or_poisoning"
],
[
"clinical_drug",
"causes",
"injury_or_poisoning"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"associated_with",
"injury_or_poisoning"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"causes",
"injury_or_poisoning"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"drug_delivery_device",
"prevents",
"injury_or_poisoning"
],
[
"drug_delivery_device",
"treats",
"injury_or_poisoning"
],
[
"educational_activity",
"associated_with",
"injury_or_poisoning"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"part_of",
"mammal"
],
[
"environmental_effect_of_humans",
"isa",
"event"
],
[
"environmental_effect_of_humans",
"isa",
"human_caused_phenomenon_or_process"
],
[
"environmental_effect_of_humans",
"result_of",
"human_caused_phenomenon_or_process"
],
[
"environmental_effect_of_humans",
"result_of",
"injury_or_poisoning"
],
[
"finding",
"associated_with",
"injury_or_poisoning"
],
[
"finding",
"isa",
"conceptual_entity"
],
[
"finding",
"manifestation_of",
"injury_or_poisoning"
],
[
"food",
"causes",
"injury_or_poisoning"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"geographic_area",
"associated_with",
"injury_or_poisoning"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"governmental_or_regulatory_activity",
"associated_with",
"injury_or_poisoning"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"human_caused_phenomenon_or_process",
"isa",
"event"
],
[
"human_caused_phenomenon_or_process",
"result_of",
"environmental_effect_of_humans"
],
[
"human_caused_phenomenon_or_process",
"result_of",
"injury_or_poisoning"
],
[
"injury_or_poisoning",
"disrupts",
"embryonic_structure"
],
[
"injury_or_poisoning",
"isa",
"event"
],
[
"injury_or_poisoning",
"result_of",
"environmental_effect_of_humans"
],
[
"injury_or_poisoning",
"result_of",
"human_caused_phenomenon_or_process"
],
[
"inorganic_chemical",
"causes",
"injury_or_poisoning"
],
[
"inorganic_chemical",
"ingredient_of",
"clinical_drug"
],
[
"inorganic_chemical",
"isa",
"substance"
],
[
"manufactured_object",
"causes",
"injury_or_poisoning"
],
[
"medical_device",
"causes",
"injury_or_poisoning"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"medical_device",
"prevents",
"injury_or_poisoning"
],
[
"medical_device",
"treats",
"injury_or_poisoning"
],
[
"occupational_activity",
"associated_with",
"injury_or_poisoning"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"body_space_or_junction"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"research_device",
"causes",
"injury_or_poisoning"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"substance",
"causes",
"injury_or_poisoning"
],
[
"substance",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
132, body_system
37, mammal
4, tissue
src, edge_attr, dst
4, conceptual_part_of, 132
4, part_of, 37
Question: For what reason are body_system, mammal, and tissue associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"body_system",
"mammal",
"tissue"
],
"valid_edges": [
[
"tissue",
"conceptual_part_of",
"body_system"
],
[
"tissue",
"part_of",
"mammal"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
28, age_group
64, behavior
48, classification
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
50, event
124, family_group
82, functional_concept
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
70, idea_or_concept
55, intellectual_product
36, machine_activity
113, manufactured_object
59, medical_device
27, occupational_activity
111, qualitative_concept
66, regulation_or_law
67, research_device
122, social_behavior
0, vitamin
src, edge_attr, dst
69, isa, 50
28, exhibits, 64
28, exhibits, 122
28, isa, 17
28, performs, 69
28, performs, 64
28, performs, 24
28, performs, 107
28, performs, 91
28, performs, 53
28, performs, 36
28, performs, 27
28, performs, 122
28, produces, 48
28, produces, 61
28, produces, 68
28, produces, 55
28, produces, 113
28, produces, 59
28, produces, 66
28, produces, 67
28, uses, 48
28, uses, 61
28, uses, 68
28, uses, 55
28, uses, 113
28, uses, 59
28, uses, 66
28, uses, 67
64, affects, 122
64, associated_with, 28
64, associated_with, 124
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
48, isa, 17
61, isa, 113
24, isa, 69
24, isa, 50
68, contains, 61
107, isa, 69
107, isa, 50
124, exhibits, 64
124, exhibits, 122
124, interacts_with, 28
124, isa, 17
124, performs, 69
124, performs, 64
124, performs, 24
124, performs, 107
124, performs, 91
124, performs, 53
124, performs, 36
124, performs, 27
124, performs, 122
124, produces, 48
124, produces, 61
124, produces, 68
124, produces, 55
124, produces, 113
124, produces, 59
124, produces, 66
124, produces, 67
124, uses, 48
124, uses, 61
124, uses, 68
124, uses, 55
124, uses, 113
124, uses, 59
124, uses, 66
124, uses, 67
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
91, isa, 69
91, isa, 50
10, isa, 17
10, property_of, 28
10, property_of, 124
53, isa, 69
53, isa, 50
70, conceptual_part_of, 64
70, isa, 17
55, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
111, isa, 70
66, affects, 28
66, affects, 124
66, isa, 17
122, affects, 64
122, associated_with, 28
122, associated_with, 124
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
0, ingredient_of, 61
Question: For what reason are functional_concept, social_behavior, and vitamin associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"functional_concept",
"social_behavior",
"vitamin"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"age_group",
"exhibits",
"behavior"
],
[
"age_group",
"exhibits",
"social_behavior"
],
[
"age_group",
"isa",
"conceptual_entity"
],
[
"age_group",
"performs",
"activity"
],
[
"age_group",
"performs",
"behavior"
],
[
"age_group",
"performs",
"daily_or_recreational_activity"
],
[
"age_group",
"performs",
"educational_activity"
],
[
"age_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"age_group",
"performs",
"health_care_activity"
],
[
"age_group",
"performs",
"machine_activity"
],
[
"age_group",
"performs",
"occupational_activity"
],
[
"age_group",
"performs",
"social_behavior"
],
[
"age_group",
"produces",
"classification"
],
[
"age_group",
"produces",
"clinical_drug"
],
[
"age_group",
"produces",
"drug_delivery_device"
],
[
"age_group",
"produces",
"intellectual_product"
],
[
"age_group",
"produces",
"manufactured_object"
],
[
"age_group",
"produces",
"medical_device"
],
[
"age_group",
"produces",
"regulation_or_law"
],
[
"age_group",
"produces",
"research_device"
],
[
"age_group",
"uses",
"classification"
],
[
"age_group",
"uses",
"clinical_drug"
],
[
"age_group",
"uses",
"drug_delivery_device"
],
[
"age_group",
"uses",
"intellectual_product"
],
[
"age_group",
"uses",
"manufactured_object"
],
[
"age_group",
"uses",
"medical_device"
],
[
"age_group",
"uses",
"regulation_or_law"
],
[
"age_group",
"uses",
"research_device"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"age_group"
],
[
"behavior",
"associated_with",
"family_group"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"classification",
"isa",
"conceptual_entity"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"family_group",
"exhibits",
"behavior"
],
[
"family_group",
"exhibits",
"social_behavior"
],
[
"family_group",
"interacts_with",
"age_group"
],
[
"family_group",
"isa",
"conceptual_entity"
],
[
"family_group",
"performs",
"activity"
],
[
"family_group",
"performs",
"behavior"
],
[
"family_group",
"performs",
"daily_or_recreational_activity"
],
[
"family_group",
"performs",
"educational_activity"
],
[
"family_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"family_group",
"performs",
"health_care_activity"
],
[
"family_group",
"performs",
"machine_activity"
],
[
"family_group",
"performs",
"occupational_activity"
],
[
"family_group",
"performs",
"social_behavior"
],
[
"family_group",
"produces",
"classification"
],
[
"family_group",
"produces",
"clinical_drug"
],
[
"family_group",
"produces",
"drug_delivery_device"
],
[
"family_group",
"produces",
"intellectual_product"
],
[
"family_group",
"produces",
"manufactured_object"
],
[
"family_group",
"produces",
"medical_device"
],
[
"family_group",
"produces",
"regulation_or_law"
],
[
"family_group",
"produces",
"research_device"
],
[
"family_group",
"uses",
"classification"
],
[
"family_group",
"uses",
"clinical_drug"
],
[
"family_group",
"uses",
"drug_delivery_device"
],
[
"family_group",
"uses",
"intellectual_product"
],
[
"family_group",
"uses",
"manufactured_object"
],
[
"family_group",
"uses",
"medical_device"
],
[
"family_group",
"uses",
"regulation_or_law"
],
[
"family_group",
"uses",
"research_device"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"group_attribute",
"property_of",
"age_group"
],
[
"group_attribute",
"property_of",
"family_group"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"intellectual_product",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"regulation_or_law",
"affects",
"age_group"
],
[
"regulation_or_law",
"affects",
"family_group"
],
[
"regulation_or_law",
"isa",
"conceptual_entity"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"age_group"
],
[
"social_behavior",
"associated_with",
"family_group"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"vitamin",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
123, diagnostic_procedure
16, group
21, hormone
src, edge_attr, dst
123, analyzes, 21
123, assesses_effect_of, 21
123, measures, 21
16, performs, 123
Question: How are diagnostic_procedure, group, and hormone related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"diagnostic_procedure",
"group",
"hormone"
],
"valid_edges": [
[
"diagnostic_procedure",
"analyzes",
"hormone"
],
[
"diagnostic_procedure",
"assesses_effect_of",
"hormone"
],
[
"diagnostic_procedure",
"measures",
"hormone"
],
[
"group",
"performs",
"diagnostic_procedure"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
9, entity
52, laboratory_or_test_result
77, neuroreactive_substance_or_biogenic_amine
src, edge_attr, dst
52, isa, 9
52, measurement_of, 77
77, isa, 9
Question: How are entity, laboratory_or_test_result, and neuroreactive_substance_or_biogenic_amine related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"entity",
"laboratory_or_test_result",
"neuroreactive_substance_or_biogenic_amine"
],
"valid_edges": [
[
"laboratory_or_test_result",
"isa",
"entity"
],
[
"laboratory_or_test_result",
"measurement_of",
"neuroreactive_substance_or_biogenic_amine"
],
[
"neuroreactive_substance_or_biogenic_amine",
"isa",
"entity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
36, machine_activity
31, organization
23, professional_or_occupational_group
111, qualitative_concept
src, edge_attr, dst
23, manages, 31
23, performs, 36
111, evaluation_of, 36
Question: For what reason are organization, professional_or_occupational_group, and qualitative_concept associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"organization",
"professional_or_occupational_group",
"qualitative_concept"
],
"valid_edges": [
[
"professional_or_occupational_group",
"manages",
"organization"
],
[
"professional_or_occupational_group",
"performs",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
116, bird
47, enzyme
4, tissue
src, edge_attr, dst
47, disrupts, 4
4, part_of, 116
4, produces, 47
Question: In what context are bird, enzyme, and tissue connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bird",
"enzyme",
"tissue"
],
"valid_edges": [
[
"enzyme",
"disrupts",
"tissue"
],
[
"tissue",
"part_of",
"bird"
],
[
"tissue",
"produces",
"enzyme"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
22, anatomical_structure
64, behavior
116, bird
17, conceptual_entity
24, daily_or_recreational_activity
107, educational_activity
88, embryonic_structure
43, environmental_effect_of_humans
50, event
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
128, health_care_related_organization
45, human_caused_phenomenon_or_process
70, idea_or_concept
36, machine_activity
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
40, self_help_or_relief_organization
122, social_behavior
src, edge_attr, dst
69, isa, 50
22, part_of, 116
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
116, exhibits, 64
116, exhibits, 122
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
107, isa, 27
88, isa, 22
88, part_of, 116
43, isa, 50
43, isa, 45
43, result_of, 45
42, isa, 17
91, isa, 69
91, isa, 50
91, isa, 27
10, isa, 17
53, isa, 69
53, isa, 50
53, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 53
128, carries_out, 27
128, isa, 17
128, location_of, 107
128, location_of, 91
128, location_of, 53
128, location_of, 27
45, isa, 50
45, result_of, 43
70, conceptual_part_of, 64
70, isa, 17
36, isa, 69
36, isa, 50
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 53
31, carries_out, 27
31, isa, 17
31, location_of, 107
31, location_of, 91
31, location_of, 53
31, location_of, 27
41, carries_out, 107
41, carries_out, 91
41, carries_out, 53
41, carries_out, 27
41, isa, 17
41, location_of, 107
41, location_of, 91
41, location_of, 53
41, location_of, 27
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, isa, 17
40, carries_out, 107
40, carries_out, 91
40, carries_out, 53
40, carries_out, 27
40, isa, 17
40, location_of, 107
40, location_of, 91
40, location_of, 53
40, location_of, 27
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
Question: For what reason are bird, event, and group_attribute associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bird",
"event",
"group_attribute"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"anatomical_structure",
"part_of",
"bird"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"bird",
"exhibits",
"behavior"
],
[
"bird",
"exhibits",
"social_behavior"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"part_of",
"bird"
],
[
"environmental_effect_of_humans",
"isa",
"event"
],
[
"environmental_effect_of_humans",
"isa",
"human_caused_phenomenon_or_process"
],
[
"environmental_effect_of_humans",
"result_of",
"human_caused_phenomenon_or_process"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"group_attribute",
"isa",
"conceptual_entity"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"health_care_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"isa",
"conceptual_entity"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"health_care_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"human_caused_phenomenon_or_process",
"isa",
"event"
],
[
"human_caused_phenomenon_or_process",
"result_of",
"environmental_effect_of_humans"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"health_care_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"isa",
"conceptual_entity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"health_care_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"health_care_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"isa",
"conceptual_entity"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"health_care_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"isa",
"conceptual_entity"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"health_care_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
109, genetic_function
117, receptor
20, steroid
src, edge_attr, dst
109, produces, 117
117, affects, 109
117, complicates, 109
117, disrupts, 109
20, affects, 109
20, interacts_with, 117
Question: For what reason are genetic_function, receptor, and steroid associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"genetic_function",
"receptor",
"steroid"
],
"valid_edges": [
[
"genetic_function",
"produces",
"receptor"
],
[
"receptor",
"affects",
"genetic_function"
],
[
"receptor",
"complicates",
"genetic_function"
],
[
"receptor",
"disrupts",
"genetic_function"
],
[
"steroid",
"affects",
"genetic_function"
],
[
"steroid",
"interacts_with",
"receptor"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
57, amino_acid_peptide_or_protein
24, daily_or_recreational_activity
107, educational_activity
50, event
109, genetic_function
91, governmental_or_regulatory_activity
128, health_care_related_organization
36, machine_activity
31, organization
23, professional_or_occupational_group
41, professional_society
111, qualitative_concept
40, self_help_or_relief_organization
src, edge_attr, dst
69, isa, 50
57, affects, 109
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
109, isa, 50
91, isa, 69
91, isa, 50
128, carries_out, 107
128, carries_out, 91
128, isa, 31
128, location_of, 107
128, location_of, 91
36, isa, 69
36, isa, 50
31, carries_out, 107
31, carries_out, 91
31, location_of, 107
31, location_of, 91
23, manages, 128
23, manages, 31
23, manages, 41
23, manages, 40
23, performs, 69
23, performs, 24
23, performs, 107
23, performs, 91
23, performs, 36
41, carries_out, 107
41, carries_out, 91
41, isa, 31
41, location_of, 107
41, location_of, 91
111, evaluation_of, 69
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 36
40, carries_out, 107
40, carries_out, 91
40, isa, 31
40, location_of, 107
40, location_of, 91
Question: For what reason are amino_acid_peptide_or_protein, genetic_function, and professional_or_occupational_group associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"amino_acid_peptide_or_protein",
"genetic_function",
"professional_or_occupational_group"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"amino_acid_peptide_or_protein",
"affects",
"genetic_function"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"genetic_function",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_or_occupational_group",
"manages",
"health_care_related_organization"
],
[
"professional_or_occupational_group",
"manages",
"organization"
],
[
"professional_or_occupational_group",
"manages",
"professional_society"
],
[
"professional_or_occupational_group",
"manages",
"self_help_or_relief_organization"
],
[
"professional_or_occupational_group",
"performs",
"activity"
],
[
"professional_or_occupational_group",
"performs",
"daily_or_recreational_activity"
],
[
"professional_or_occupational_group",
"performs",
"educational_activity"
],
[
"professional_or_occupational_group",
"performs",
"governmental_or_regulatory_activity"
],
[
"professional_or_occupational_group",
"performs",
"machine_activity"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
26, amino_acid_sequence
94, body_location_or_region
132, body_system
3, carbohydrate_sequence
17, conceptual_entity
82, functional_concept
42, geographic_area
70, idea_or_concept
32, molecular_sequence
134, nucleotide_sequence
131, organism_attribute
111, qualitative_concept
96, quantitative_concept
79, spatial_concept
108, temporal_concept
src, edge_attr, dst
26, isa, 17
26, isa, 70
26, isa, 32
26, isa, 79
94, isa, 17
94, isa, 70
94, isa, 79
132, isa, 17
132, isa, 70
3, isa, 17
3, isa, 70
3, isa, 32
3, isa, 79
82, isa, 17
82, isa, 70
42, isa, 17
42, isa, 70
42, isa, 79
70, isa, 17
32, isa, 17
32, isa, 70
32, isa, 79
134, isa, 17
134, isa, 70
134, isa, 32
134, isa, 79
131, isa, 17
111, isa, 17
111, isa, 70
96, isa, 17
96, isa, 70
96, measurement_of, 26
96, measurement_of, 94
96, measurement_of, 3
96, measurement_of, 42
96, measurement_of, 32
96, measurement_of, 134
96, measurement_of, 79
79, isa, 17
79, isa, 70
108, isa, 17
108, isa, 70
Question: How are molecular_sequence, nucleotide_sequence, and organism_attribute related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"molecular_sequence",
"nucleotide_sequence",
"organism_attribute"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"conceptual_entity"
],
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_system",
"isa",
"conceptual_entity"
],
[
"body_system",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"conceptual_entity"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"functional_concept",
"isa",
"conceptual_entity"
],
[
"functional_concept",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"idea_or_concept",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"conceptual_entity"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"conceptual_entity"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"organism_attribute",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"amino_acid_sequence"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"carbohydrate_sequence"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"quantitative_concept",
"measurement_of",
"molecular_sequence"
],
[
"quantitative_concept",
"measurement_of",
"nucleotide_sequence"
],
[
"quantitative_concept",
"measurement_of",
"spatial_concept"
],
[
"spatial_concept",
"isa",
"conceptual_entity"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
],
[
"temporal_concept",
"isa",
"conceptual_entity"
],
[
"temporal_concept",
"isa",
"idea_or_concept"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
112, alga
64, behavior
17, conceptual_entity
24, daily_or_recreational_activity
107, educational_activity
50, event
42, geographic_area
91, governmental_or_regulatory_activity
10, group_attribute
53, health_care_activity
100, human
70, idea_or_concept
36, machine_activity
27, occupational_activity
111, qualitative_concept
96, quantitative_concept
122, social_behavior
7, therapeutic_or_preventive_procedure
src, edge_attr, dst
69, isa, 50
112, interacts_with, 100
64, affects, 122
64, associated_with, 42
64, associated_with, 10
64, isa, 69
64, isa, 50
24, isa, 69
24, isa, 50
107, isa, 69
107, isa, 50
107, isa, 27
91, isa, 69
91, isa, 50
91, isa, 27
53, isa, 69
53, isa, 50
53, isa, 27
100, exhibits, 64
100, exhibits, 122
70, conceptual_part_of, 64
36, isa, 69
36, isa, 50
36, method_of, 7
27, isa, 69
27, isa, 50
111, evaluation_of, 69
111, evaluation_of, 64
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 53
111, evaluation_of, 36
111, evaluation_of, 27
111, evaluation_of, 122
111, evaluation_of, 7
111, isa, 17
111, isa, 70
96, conceptual_part_of, 7
96, isa, 17
96, isa, 70
96, measurement_of, 42
122, affects, 64
122, associated_with, 42
122, associated_with, 10
122, isa, 69
122, isa, 64
122, isa, 50
7, isa, 69
7, isa, 50
7, isa, 53
7, isa, 27
Question: How are alga, human, and therapeutic_or_preventive_procedure related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"alga",
"human",
"therapeutic_or_preventive_procedure"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"alga",
"interacts_with",
"human"
],
[
"behavior",
"affects",
"social_behavior"
],
[
"behavior",
"associated_with",
"geographic_area"
],
[
"behavior",
"associated_with",
"group_attribute"
],
[
"behavior",
"isa",
"activity"
],
[
"behavior",
"isa",
"event"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"health_care_activity",
"isa",
"activity"
],
[
"health_care_activity",
"isa",
"event"
],
[
"health_care_activity",
"isa",
"occupational_activity"
],
[
"human",
"exhibits",
"behavior"
],
[
"human",
"exhibits",
"social_behavior"
],
[
"idea_or_concept",
"conceptual_part_of",
"behavior"
],
[
"machine_activity",
"isa",
"activity"
],
[
"machine_activity",
"isa",
"event"
],
[
"machine_activity",
"method_of",
"therapeutic_or_preventive_procedure"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"qualitative_concept",
"evaluation_of",
"activity"
],
[
"qualitative_concept",
"evaluation_of",
"behavior"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"health_care_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"social_behavior"
],
[
"qualitative_concept",
"evaluation_of",
"therapeutic_or_preventive_procedure"
],
[
"qualitative_concept",
"isa",
"conceptual_entity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"conceptual_part_of",
"therapeutic_or_preventive_procedure"
],
[
"quantitative_concept",
"isa",
"conceptual_entity"
],
[
"quantitative_concept",
"isa",
"idea_or_concept"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"social_behavior",
"affects",
"behavior"
],
[
"social_behavior",
"associated_with",
"geographic_area"
],
[
"social_behavior",
"associated_with",
"group_attribute"
],
[
"social_behavior",
"isa",
"activity"
],
[
"social_behavior",
"isa",
"behavior"
],
[
"social_behavior",
"isa",
"event"
],
[
"therapeutic_or_preventive_procedure",
"isa",
"activity"
],
[
"therapeutic_or_preventive_procedure",
"isa",
"event"
],
[
"therapeutic_or_preventive_procedure",
"isa",
"health_care_activity"
],
[
"therapeutic_or_preventive_procedure",
"isa",
"occupational_activity"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
9, entity
38, organic_chemical
4, tissue
src, edge_attr, dst
38, isa, 9
4, isa, 9
4, produces, 38
Question: For what reason are entity, organic_chemical, and tissue associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"entity",
"organic_chemical",
"tissue"
],
"valid_edges": [
[
"organic_chemical",
"isa",
"entity"
],
[
"tissue",
"isa",
"entity"
],
[
"tissue",
"produces",
"organic_chemical"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
116, bird
97, injury_or_poisoning
126, physical_object
67, research_device
src, edge_attr, dst
116, isa, 126
67, causes, 97
67, isa, 126
Question: For what reason are bird, injury_or_poisoning, and physical_object associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"bird",
"injury_or_poisoning",
"physical_object"
],
"valid_edges": [
[
"bird",
"isa",
"physical_object"
],
[
"research_device",
"causes",
"injury_or_poisoning"
],
[
"research_device",
"isa",
"physical_object"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
60, biologic_function
100, human
19, molecular_biology_research_technique
src, edge_attr, dst
60, affects, 100
60, process_of, 100
19, measures, 60
Question: How are biologic_function, human, and molecular_biology_research_technique related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"biologic_function",
"human",
"molecular_biology_research_technique"
],
"valid_edges": [
[
"biologic_function",
"affects",
"human"
],
[
"biologic_function",
"process_of",
"human"
],
[
"molecular_biology_research_technique",
"measures",
"biologic_function"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
95, acquired_abnormality
69, activity
90, antibiotic
48, classification
24, daily_or_recreational_activity
107, educational_activity
91, governmental_or_regulatory_activity
128, health_care_related_organization
55, intellectual_product
113, manufactured_object
31, organization
41, professional_society
111, qualitative_concept
66, regulation_or_law
67, research_device
40, self_help_or_relief_organization
src, edge_attr, dst
90, causes, 95
90, complicates, 95
90, treats, 95
48, isa, 55
24, associated_with, 95
24, isa, 69
107, associated_with, 95
107, isa, 69
91, associated_with, 95
91, isa, 69
128, carries_out, 107
128, carries_out, 91
128, isa, 31
128, location_of, 107
128, location_of, 91
128, produces, 48
128, produces, 55
128, produces, 66
113, causes, 95
31, carries_out, 107
31, carries_out, 91
31, location_of, 107
31, location_of, 91
31, produces, 48
31, produces, 55
31, produces, 66
41, carries_out, 107
41, carries_out, 91
41, isa, 31
41, location_of, 107
41, location_of, 91
41, produces, 48
41, produces, 55
41, produces, 66
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
66, affects, 128
66, affects, 31
66, affects, 41
66, affects, 40
66, isa, 55
67, causes, 95
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, isa, 31
40, location_of, 107
40, location_of, 91
40, produces, 48
40, produces, 55
40, produces, 66
Question: How are acquired_abnormality, antibiotic, and self_help_or_relief_organization related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"acquired_abnormality",
"antibiotic",
"self_help_or_relief_organization"
],
"valid_edges": [
[
"antibiotic",
"causes",
"acquired_abnormality"
],
[
"antibiotic",
"complicates",
"acquired_abnormality"
],
[
"antibiotic",
"treats",
"acquired_abnormality"
],
[
"classification",
"isa",
"intellectual_product"
],
[
"daily_or_recreational_activity",
"associated_with",
"acquired_abnormality"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"educational_activity",
"associated_with",
"acquired_abnormality"
],
[
"educational_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"associated_with",
"acquired_abnormality"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"isa",
"organization"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"produces",
"classification"
],
[
"health_care_related_organization",
"produces",
"intellectual_product"
],
[
"health_care_related_organization",
"produces",
"regulation_or_law"
],
[
"manufactured_object",
"causes",
"acquired_abnormality"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"produces",
"classification"
],
[
"organization",
"produces",
"intellectual_product"
],
[
"organization",
"produces",
"regulation_or_law"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"isa",
"organization"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"produces",
"classification"
],
[
"professional_society",
"produces",
"intellectual_product"
],
[
"professional_society",
"produces",
"regulation_or_law"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"regulation_or_law",
"affects",
"health_care_related_organization"
],
[
"regulation_or_law",
"affects",
"organization"
],
[
"regulation_or_law",
"affects",
"professional_society"
],
[
"regulation_or_law",
"affects",
"self_help_or_relief_organization"
],
[
"regulation_or_law",
"isa",
"intellectual_product"
],
[
"research_device",
"causes",
"acquired_abnormality"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"isa",
"organization"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"produces",
"classification"
],
[
"self_help_or_relief_organization",
"produces",
"intellectual_product"
],
[
"self_help_or_relief_organization",
"produces",
"regulation_or_law"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
95, acquired_abnormality
116, bird
100, human
src, edge_attr, dst
95, affects, 116
95, affects, 100
95, part_of, 116
95, part_of, 100
116, interacts_with, 100
Question: In what context are acquired_abnormality, bird, and human connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"acquired_abnormality",
"bird",
"human"
],
"valid_edges": [
[
"acquired_abnormality",
"affects",
"bird"
],
[
"acquired_abnormality",
"affects",
"human"
],
[
"acquired_abnormality",
"part_of",
"bird"
],
[
"acquired_abnormality",
"part_of",
"human"
],
[
"bird",
"interacts_with",
"human"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
105, anatomical_abnormality
92, cell
67, research_device
src, edge_attr, dst
92, location_of, 105
67, causes, 105
Question: How are anatomical_abnormality, cell, and research_device related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"anatomical_abnormality",
"cell",
"research_device"
],
"valid_edges": [
[
"cell",
"location_of",
"anatomical_abnormality"
],
[
"research_device",
"causes",
"anatomical_abnormality"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
69, activity
22, anatomical_structure
94, body_location_or_region
103, body_space_or_junction
132, body_system
61, clinical_drug
17, conceptual_entity
24, daily_or_recreational_activity
68, drug_delivery_device
107, educational_activity
88, embryonic_structure
43, environmental_effect_of_humans
50, event
89, finding
75, food
46, fungus
42, geographic_area
91, governmental_or_regulatory_activity
128, health_care_related_organization
45, human_caused_phenomenon_or_process
70, idea_or_concept
97, injury_or_poisoning
113, manufactured_object
59, medical_device
27, occupational_activity
31, organization
41, professional_society
111, qualitative_concept
96, quantitative_concept
67, research_device
40, self_help_or_relief_organization
79, spatial_concept
84, substance
src, edge_attr, dst
69, isa, 50
22, location_of, 46
22, part_of, 46
94, adjacent_to, 103
94, conceptual_part_of, 132
94, isa, 17
94, isa, 70
94, isa, 79
94, location_of, 97
103, conceptual_part_of, 132
103, isa, 17
103, isa, 70
103, isa, 79
103, location_of, 97
61, causes, 97
61, isa, 113
24, associated_with, 97
24, isa, 69
24, isa, 50
68, causes, 97
68, contains, 61
68, isa, 113
68, isa, 59
68, prevents, 97
68, treats, 97
107, associated_with, 97
107, isa, 69
107, isa, 50
107, isa, 27
88, isa, 22
88, location_of, 46
88, part_of, 46
43, isa, 50
43, isa, 45
43, result_of, 45
43, result_of, 97
89, associated_with, 97
89, isa, 17
89, manifestation_of, 97
75, causes, 97
75, ingredient_of, 61
75, isa, 84
42, associated_with, 97
42, isa, 17
42, isa, 70
42, isa, 79
91, associated_with, 97
91, isa, 69
91, isa, 50
91, isa, 27
128, carries_out, 107
128, carries_out, 91
128, carries_out, 27
128, location_of, 107
128, location_of, 91
128, location_of, 27
45, isa, 50
45, result_of, 43
45, result_of, 97
97, disrupts, 88
97, isa, 50
97, result_of, 43
97, result_of, 45
113, causes, 97
59, causes, 97
59, isa, 113
59, prevents, 97
59, treats, 97
27, associated_with, 97
27, isa, 69
27, isa, 50
31, carries_out, 107
31, carries_out, 91
31, carries_out, 27
31, location_of, 107
31, location_of, 91
31, location_of, 27
41, carries_out, 107
41, carries_out, 91
41, carries_out, 27
41, location_of, 107
41, location_of, 91
41, location_of, 27
111, evaluation_of, 24
111, evaluation_of, 107
111, evaluation_of, 91
111, evaluation_of, 27
96, measurement_of, 94
96, measurement_of, 103
96, measurement_of, 42
67, causes, 97
67, isa, 113
40, carries_out, 107
40, carries_out, 91
40, carries_out, 27
40, location_of, 107
40, location_of, 91
40, location_of, 27
84, causes, 97
84, ingredient_of, 61
Question: In what context are anatomical_structure, fungus, and injury_or_poisoning connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"anatomical_structure",
"fungus",
"injury_or_poisoning"
],
"valid_edges": [
[
"activity",
"isa",
"event"
],
[
"anatomical_structure",
"location_of",
"fungus"
],
[
"anatomical_structure",
"part_of",
"fungus"
],
[
"body_location_or_region",
"adjacent_to",
"body_space_or_junction"
],
[
"body_location_or_region",
"conceptual_part_of",
"body_system"
],
[
"body_location_or_region",
"isa",
"conceptual_entity"
],
[
"body_location_or_region",
"isa",
"idea_or_concept"
],
[
"body_location_or_region",
"isa",
"spatial_concept"
],
[
"body_location_or_region",
"location_of",
"injury_or_poisoning"
],
[
"body_space_or_junction",
"conceptual_part_of",
"body_system"
],
[
"body_space_or_junction",
"isa",
"conceptual_entity"
],
[
"body_space_or_junction",
"isa",
"idea_or_concept"
],
[
"body_space_or_junction",
"isa",
"spatial_concept"
],
[
"body_space_or_junction",
"location_of",
"injury_or_poisoning"
],
[
"clinical_drug",
"causes",
"injury_or_poisoning"
],
[
"clinical_drug",
"isa",
"manufactured_object"
],
[
"daily_or_recreational_activity",
"associated_with",
"injury_or_poisoning"
],
[
"daily_or_recreational_activity",
"isa",
"activity"
],
[
"daily_or_recreational_activity",
"isa",
"event"
],
[
"drug_delivery_device",
"causes",
"injury_or_poisoning"
],
[
"drug_delivery_device",
"contains",
"clinical_drug"
],
[
"drug_delivery_device",
"isa",
"manufactured_object"
],
[
"drug_delivery_device",
"isa",
"medical_device"
],
[
"drug_delivery_device",
"prevents",
"injury_or_poisoning"
],
[
"drug_delivery_device",
"treats",
"injury_or_poisoning"
],
[
"educational_activity",
"associated_with",
"injury_or_poisoning"
],
[
"educational_activity",
"isa",
"activity"
],
[
"educational_activity",
"isa",
"event"
],
[
"educational_activity",
"isa",
"occupational_activity"
],
[
"embryonic_structure",
"isa",
"anatomical_structure"
],
[
"embryonic_structure",
"location_of",
"fungus"
],
[
"embryonic_structure",
"part_of",
"fungus"
],
[
"environmental_effect_of_humans",
"isa",
"event"
],
[
"environmental_effect_of_humans",
"isa",
"human_caused_phenomenon_or_process"
],
[
"environmental_effect_of_humans",
"result_of",
"human_caused_phenomenon_or_process"
],
[
"environmental_effect_of_humans",
"result_of",
"injury_or_poisoning"
],
[
"finding",
"associated_with",
"injury_or_poisoning"
],
[
"finding",
"isa",
"conceptual_entity"
],
[
"finding",
"manifestation_of",
"injury_or_poisoning"
],
[
"food",
"causes",
"injury_or_poisoning"
],
[
"food",
"ingredient_of",
"clinical_drug"
],
[
"food",
"isa",
"substance"
],
[
"geographic_area",
"associated_with",
"injury_or_poisoning"
],
[
"geographic_area",
"isa",
"conceptual_entity"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"governmental_or_regulatory_activity",
"associated_with",
"injury_or_poisoning"
],
[
"governmental_or_regulatory_activity",
"isa",
"activity"
],
[
"governmental_or_regulatory_activity",
"isa",
"event"
],
[
"governmental_or_regulatory_activity",
"isa",
"occupational_activity"
],
[
"health_care_related_organization",
"carries_out",
"educational_activity"
],
[
"health_care_related_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"carries_out",
"occupational_activity"
],
[
"health_care_related_organization",
"location_of",
"educational_activity"
],
[
"health_care_related_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"health_care_related_organization",
"location_of",
"occupational_activity"
],
[
"human_caused_phenomenon_or_process",
"isa",
"event"
],
[
"human_caused_phenomenon_or_process",
"result_of",
"environmental_effect_of_humans"
],
[
"human_caused_phenomenon_or_process",
"result_of",
"injury_or_poisoning"
],
[
"injury_or_poisoning",
"disrupts",
"embryonic_structure"
],
[
"injury_or_poisoning",
"isa",
"event"
],
[
"injury_or_poisoning",
"result_of",
"environmental_effect_of_humans"
],
[
"injury_or_poisoning",
"result_of",
"human_caused_phenomenon_or_process"
],
[
"manufactured_object",
"causes",
"injury_or_poisoning"
],
[
"medical_device",
"causes",
"injury_or_poisoning"
],
[
"medical_device",
"isa",
"manufactured_object"
],
[
"medical_device",
"prevents",
"injury_or_poisoning"
],
[
"medical_device",
"treats",
"injury_or_poisoning"
],
[
"occupational_activity",
"associated_with",
"injury_or_poisoning"
],
[
"occupational_activity",
"isa",
"activity"
],
[
"occupational_activity",
"isa",
"event"
],
[
"organization",
"carries_out",
"educational_activity"
],
[
"organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"organization",
"carries_out",
"occupational_activity"
],
[
"organization",
"location_of",
"educational_activity"
],
[
"organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"organization",
"location_of",
"occupational_activity"
],
[
"professional_society",
"carries_out",
"educational_activity"
],
[
"professional_society",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"carries_out",
"occupational_activity"
],
[
"professional_society",
"location_of",
"educational_activity"
],
[
"professional_society",
"location_of",
"governmental_or_regulatory_activity"
],
[
"professional_society",
"location_of",
"occupational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"educational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"governmental_or_regulatory_activity"
],
[
"qualitative_concept",
"evaluation_of",
"occupational_activity"
],
[
"quantitative_concept",
"measurement_of",
"body_location_or_region"
],
[
"quantitative_concept",
"measurement_of",
"body_space_or_junction"
],
[
"quantitative_concept",
"measurement_of",
"geographic_area"
],
[
"research_device",
"causes",
"injury_or_poisoning"
],
[
"research_device",
"isa",
"manufactured_object"
],
[
"self_help_or_relief_organization",
"carries_out",
"educational_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"carries_out",
"occupational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"educational_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"governmental_or_regulatory_activity"
],
[
"self_help_or_relief_organization",
"location_of",
"occupational_activity"
],
[
"substance",
"causes",
"injury_or_poisoning"
],
[
"substance",
"ingredient_of",
"clinical_drug"
]
]
}
|
UMLS
|
You are given a directed graph as two CSV-like sections in this order:
1) Node table (header included):
node_id, node_attr
2) Edge table (header included):
src, edge_attr, dst
Task
- Use ONLY edges from the Edge table to answer the question by outputting a path.
- When printing each edge, replace IDs with the exact node_attr from the Node table.
- Output MUST be text triples, not numeric IDs.
Output format (STRICT — no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs → node_attr; preserve node_attr exactly.
- Output NOTHING outside the PATH block.
- If no path exists, output exactly:
PATH:
END
Graph:
node_id, node_attr
26, amino_acid_sequence
3, carbohydrate_sequence
11, cell_or_molecular_dysfunction
24, daily_or_recreational_activity
42, geographic_area
70, idea_or_concept
36, machine_activity
32, molecular_sequence
134, nucleotide_sequence
23, professional_or_occupational_group
111, qualitative_concept
79, spatial_concept
src, edge_attr, dst
26, isa, 70
26, isa, 32
26, isa, 79
3, isa, 70
3, isa, 32
3, isa, 79
11, occurs_in, 23
24, associated_with, 11
42, associated_with, 11
42, isa, 70
42, isa, 79
32, isa, 70
32, isa, 79
134, isa, 70
134, isa, 32
134, isa, 79
23, diagnoses, 11
23, performs, 24
23, performs, 36
111, evaluation_of, 24
111, evaluation_of, 36
111, isa, 70
79, isa, 70
Question: For what reason are cell_or_molecular_dysfunction, molecular_sequence, and professional_or_occupational_group associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"cell_or_molecular_dysfunction",
"molecular_sequence",
"professional_or_occupational_group"
],
"valid_edges": [
[
"amino_acid_sequence",
"isa",
"idea_or_concept"
],
[
"amino_acid_sequence",
"isa",
"molecular_sequence"
],
[
"amino_acid_sequence",
"isa",
"spatial_concept"
],
[
"carbohydrate_sequence",
"isa",
"idea_or_concept"
],
[
"carbohydrate_sequence",
"isa",
"molecular_sequence"
],
[
"carbohydrate_sequence",
"isa",
"spatial_concept"
],
[
"cell_or_molecular_dysfunction",
"occurs_in",
"professional_or_occupational_group"
],
[
"daily_or_recreational_activity",
"associated_with",
"cell_or_molecular_dysfunction"
],
[
"geographic_area",
"associated_with",
"cell_or_molecular_dysfunction"
],
[
"geographic_area",
"isa",
"idea_or_concept"
],
[
"geographic_area",
"isa",
"spatial_concept"
],
[
"molecular_sequence",
"isa",
"idea_or_concept"
],
[
"molecular_sequence",
"isa",
"spatial_concept"
],
[
"nucleotide_sequence",
"isa",
"idea_or_concept"
],
[
"nucleotide_sequence",
"isa",
"molecular_sequence"
],
[
"nucleotide_sequence",
"isa",
"spatial_concept"
],
[
"professional_or_occupational_group",
"diagnoses",
"cell_or_molecular_dysfunction"
],
[
"professional_or_occupational_group",
"performs",
"daily_or_recreational_activity"
],
[
"professional_or_occupational_group",
"performs",
"machine_activity"
],
[
"qualitative_concept",
"evaluation_of",
"daily_or_recreational_activity"
],
[
"qualitative_concept",
"evaluation_of",
"machine_activity"
],
[
"qualitative_concept",
"isa",
"idea_or_concept"
],
[
"spatial_concept",
"isa",
"idea_or_concept"
]
]
}
|
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