Datasets:

relbert
/

relation_mapping

Modalities:

Text

Time-series

Languages:

English

Size:

< 1K

Libraries:

Datasets

License:

Dataset card Viewer Files Files and versions Community

Dataset Viewer

Auto-converted to Parquet

Full Screen Viewer

Full Screen

Split (1)

test · 20 rows

id stringclasses 20 values	reference sequence	source sequence	target sequence	agreement sequence	pos sequence	target_random sequence
a1	[ "solar system", "atom" ]	[ "solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity" ]	[ "atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism" ]	[ 86.4000015258789, 100, 95.5, 86.4000015258789, 90.9000015258789, 95.5, 81.80000305175781 ]	[ "nn", "nn", "nn", "nn", "vbz", "vbz", "nn" ]	[ "electron", "revolves", "nucleus", "attracts", "atom", "charge", "electromagnetism" ]
a2	[ "water flow", "heat transfer" ]	[ "water", "flows", "pressure", "water tower", "bucket", "filling", "emptying", "hydrodynamics" ]	[ "heat", "transfers", "temperature", "burner", "kettle", "heating", "cooling", "thermodynamics" ]	[ 86.4000015258789, 95.5, 86.4000015258789, 72.69999694824219, 72.69999694824219, 95.5, 95.5, 90.9000015258789 ]	[ "nn", "vbz", "nn", "nn", "nn", "vbg", "vbg", "nn" ]	[ "burner", "kettle", "cooling", "heating", "transfers", "thermodynamics", "temperature", "heat" ]
a3	[ "waves", "sounds" ]	[ "waves", "shore", "reflects", "water", "breakwater", "rough", "calm", "crashing" ]	[ "sounds", "wall", "echoes", "air", "insulation", "loud", "quiet", "vibrating" ]	[ 86.4000015258789, 77.30000305175781, 95.5, 95.5, 81.80000305175781, 63.599998474121094, 100, 54.5 ]	[ "nns", "nn", "vbz", "nn", "nn", "jj", "jj", "vbg" ]	[ "quiet", "wall", "loud", "echoes", "vibrating", "sounds", "air", "insulation" ]
a4	[ "combustion", "respiration" ]	[ "combustion", "fire", "fuel", "burning", "hot", "intense", "oxygen", "carbon dioxide" ]	[ "respiration", "animal", "food", "breathing", "living", "vigorous", "oxygen", "carbon dioxide" ]	[ 72.69999694824219, 95.5, 90.9000015258789, 72.69999694824219, 59.099998474121094, 77.30000305175781, 77.30000305175781, 86.4000015258789 ]	[ "nn", "nn", "nn", "vbg", "jj", "jj", "nn", "nn" ]	[ "living", "oxygen", "food", "vigorous", "animal", "carbon dioxide", "respiration", "breathing" ]
a5	[ "sound", "light" ]	[ "sound", "low", "high", "echoes", "loud", "quiet", "horn" ]	[ "light", "red", "violet", "reflects", "bright", "dim", "lens" ]	[ 86.4000015258789, 50, 4.5, 100, 90.9000015258789, 77.30000305175781, 95.5 ]	[ "nn", "jj", "jj", "vbz", "jj", "jj", "nn" ]	[ "bright", "dim", "light", "reflects", "red", "violet", "lens" ]
a6	[ "projectile", "planet" ]	[ "projectile", "trajectory", "earth", "parabolic", "air", "gravity", "attracts" ]	[ "planet", "orbit", "sun", "elliptical", "space", "gravity", "attracts" ]	[ 100, 100, 100, 100, 100, 100, 90.9000015258789, 90.9000015258789 ]	[ "nn", "nn", "nn", "jj", "nn", "nn", "vbz" ]	[ "gravity", "space", "elliptical", "orbit", "attracts", "planet", "sun" ]
a7	[ "artificial selection", "natural selection" ]	[ "breeds", "selection", "conformance", "artificial", "popularity", "breeding", "domesticated" ]	[ "species", "competition", "adaptation", "natural", "fitness", "mating", "wild" ]	[ 100, 59.099998474121094, 59.099998474121094, 77.30000305175781, 54.5, 95.5, 77.30000305175781 ]	[ "nns", "nn", "nn", "jj", "nn", "vbg", "jj" ]	[ "fitness", "natural", "wild", "species", "mating", "competition", "adaptation" ]
a8	[ "billiard balls", "gas molecules" ]	[ "ball", "billiards", "speed", "table", "bouncing", "moving", "slow", "fast" ]	[ "molecules", "gas", "temperature", "container", "pressing", "moving", "cold", "hot" ]	[ 90.9000015258789, 72.69999694824219, 81.80000305175781, 95.5, 77.30000305175781, 86.4000015258789, 100, 100 ]	[ "nns", "nn", "nn", "nn", "vbg", "vbg", "jj", "jj" ]	[ "gas", "container", "moving", "hot", "molecules", "pressing", "cold", "temperature" ]
a9	[ "computer", "mind" ]	[ "computer", "processing", "erasing", "write", "read", "memory", "outputs", "inputs", "bug" ]	[ "mind", "thinking", "forgetting", "memorize", "remember", "memory", "muscles", "senses", "mistake" ]	[ 90.9000015258789, 95.5, 100, 72.69999694824219, 54.5, 81.80000305175781, 72.69999694824219, 90.9000015258789, 100 ]	[ "nn", "vbg", "vbg", "vb", "vb", "nn", "nns", "nns", "nn" ]	[ "memorize", "forgetting", "remember", "mistake", "memory", "senses", "muscles", "thinking", "mind" ]
a10	[ "slot machines", "bacterial mutation" ]	[ "slot machines", "reels", "spinning", "winning", "losing" ]	[ "bacteria", "genes", "mutating", "reproducing", "dying" ]	[ 68.19999694824219, 72.69999694824219, 86.4000015258789, 90.9000015258789, 100 ]	[ "nns", "nns", "vbg", "vbg", "vbg" ]	[ "bacteria", "reproducing", "dying", "genes", "mutating" ]
m1	[ "war", "argument" ]	[ "war", "soldier", "destroy", "fighting", "defeat", "attacks", "weapon" ]	[ "argument", "debater", "refute", "arguing", "acceptance", "criticizes", "logic" ]	[ 90.9000015258789, 100, 90.9000015258789, 95.5, 90.9000015258789, 95.5, 90.9000015258789 ]	[ "nn", "nn", "vb", "vbg", "nn", "vbg", "nn" ]	[ "argument", "arguing", "debater", "criticizes", "acceptance", "refute", "logic" ]
m2	[ "buying an item", "accepting a belief" ]	[ "buyer", "merchandise", "buying", "selling", "returning", "valuable", "worthless" ]	[ "believer", "belief", "accepting", "advocating", "rejecting", "true", "false" ]	[ 100, 90.9000015258789, 95.5, 100, 95.5, 95.5, 95.5 ]	[ "nn", "nn", "vbg", "vbg", "vbg", "jj", "jj" ]	[ "advocating", "accepting", "false", "believer", "belief", "rejecting", "true" ]
m3	[ "grounds for a building", "reasons for a theory" ]	[ "foundations", "buildings", "supporting", "solid", "weak", "crack" ]	[ "reasons", "theories", "confirming", "rational", "dubious", "flaw" ]	[ 72.69999694824219, 77.30000305175781, 95.5, 90.9000015258789, 95.5, 95.5 ]	[ "nns", "nns", "vbg", "jj", "jj", "nn" ]	[ "theories", "reasons", "dubious", "confirming", "flaw", "rational" ]
m4	[ "impediments to travel", "difficulties" ]	[ "obstructions", "destination", "route", "traveller", "traveling", "companion", "arriving" ]	[ "difficulties", "goal", "plan", "person", "problem solving", "partner", "succeeding" ]	[ 100, 100, 100, 100, 100, 100, 100 ]	[ "nns", "nn", "nn", "nn", "vbg", "nn", "vbg" ]	[ "difficulties", "problem solving", "succeeding", "goal", "plan", "person", "partner" ]
m5	[ "money", "time" ]	[ "money", "allocate", "budget", "effective", "cheap", "expansive" ]	[ "time", "invest", "schedule", "efficient", "quick", "slow" ]	[ 95.5, 86.4000015258789, 86.4000015258789, 86.4000015258789, 50, 59.099998474121094 ]	[ "nn", "vb", "nn", "jj", "jj", "jj", "jj", "jj" ]	[ "quick", "invest", "slow", "efficient", "schedule", "time" ]
m6	[ "seeds", "idea" ]	[ "seeds", "planted", "fruitful", "fruit", "grow", "wither", "blossom" ]	[ "ideas", "inspired", "productive", "product", "develop", "fail", "succeed" ]	[ 90.9000015258789, 95.5, 81.80000305175781, 95.5, 81.80000305175781, 100, 77.30000305175781 ]	[ "nns", "vbd", "jj", "nn", "vb", "vb", "vb" ]	[ "develop", "succeed", "fail", "ideas", "productive", "product", "inspired" ]
m7	[ "machine", "mind" ]	[ "machine", "working", "turned on", "turned off", "broken", "power", "repair" ]	[ "mind", "thinking", "awake", "asleep", "confused", "intelligence", "therapy" ]	[ 95.5, 100, 100, 100, 100, 95.5, 100 ]	[ "nn", "vbg", "jj", "jj", "jj", "nn", "nn" ]	[ "intelligence", "thinking", "mind", "confused", "therapy", "awake", "asleep" ]
m8	[ "object", "idea" ]	[ "object", "hold", "weight", "heavy", "light" ]	[ "idea", "understand", "analyze", "important", "trivial" ]	[ 90.9000015258789, 81.80000305175781, 81.80000305175781, 95.5, 95.5 ]	[ "nn", "vb", "vb", "jj", "jj" ]	[ "idea", "analyze", "trivial", "understand", "important" ]
m9	[ "following", "understanding" ]	[ "follow", "leader", "path", "follower", "lost", "wanders", "twisted", "straight" ]	[ "understand", "speaker", "argument", "listener", "misunderstood", "digresses", "complicated", "simple" ]	[ 100, 100, 100, 100, 86.4000015258789, 90.9000015258789, 95.5, 100 ]	[ "vb", "nn", "nn", "nn", "jj", "vbz", "jj", "jj" ]	[ "understand", "simple", "argument", "listener", "misunderstood", "complicated", "speaker", "digresses" ]
m10	[ "seeing", "understanding" ]	[ "seeing", "light", "illuminating", "darkness", "view", "hidden" ]	[ "understanding", "knowledge", "explaining", "confusion", "interpretation", "secret" ]	[ 68.19999694824219, 77.30000305175781, 86.4000015258789, 86.4000015258789, 68.19999694824219, 86.4000015258789 ]	[ "vbg", "nn", "vbg", "nn", "nn", "jj" ]	[ "knowledge", "interpretation", "explaining", "confusion", "understanding", "secret" ]

Dataset Card for "relbert/relation_mapping"

Dataset Summary

Relation Mapping is a task to choose optimal combination of word pairs (see more detail in the paper).

Relation mapping M is the set of bijective map in between two sets of terms (A and B):

[set `A`]: ("solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity")
[set `B`]: ("atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism")

[Relation Mapping `M`]
* "solar system"   -> "atom"
* "sun"            -> "nucleus"
* "planet"         -> "electron"
* "mass"           -> "charge"
* "attracts"       -> "attracts"
* "revolves"       -> "revolves"
* "gravity"        -> "electromagnetism"

Relation Mapping Problem is the task to identify the mapping M given the sets of terms A and B.

Dataset Structure

Data Instances

An example looks as follows.

{
 "id": "m10",
 "reference": ["seeing", "understanding"],
 "source": ["seeing", "light", "illuminating", "darkness", "view", "hidden"],
 "target": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"],
 "agreement": [68.2, 77.3, 86.4, 86.4, 68.2, 86.4],
 "pos": ["vbg", "nn", "vbg", "nn", "nn", "jj"],
 "target_random": ["knowledge", "interpretation", "explaining", "confusion", "understanding", "secret"]
}

source: A list of terms, which is the source of the relation mapping from.
target_random: A list of terms, where we want to find a mapping from source to.
target: A correctly ordered target_random that aligns with the source.

Given source and target_random, the task is to predict the correct order of target_random so that it matches target. In average 7 terms are in the set, so the total number of possible order is 5040.

Data Splits

name	test
relation_mapping	20

Citation Information

@article{turney2008latent,
  title={The latent relation mapping engine: Algorithm and experiments},
  author={Turney, Peter D},
  journal={Journal of Artificial Intelligence Research},
  volume={33},
  pages={615--655},
  year={2008}
}

Downloads last month: 42

Edit dataset card

Size of downloaded dataset files:

8.93 kB

Size of the auto-converted Parquet files:

9.43 kB

Number of rows: