Datasets:
				
			
			
	
			
	
		
			
	
		Tasks:
	
	
	
	
	Token Classification
	
	
	Formats:
	
	
	
		
	
	parquet
	
	
	Sub-tasks:
	
	
	
	
	named-entity-recognition
	
	
	Languages:
	
	
	
		
	
	Arabic
	
	
	Size:
	
	
	
	
	10K - 100K
	
	
	License:
	
	
	
	
	
	
	
Initial public release of ShamNER v1.0
Browse files- LICENSE +1 -0
- README.md +74 -0
- dataset_card.yaml +13 -0
- hf_data/dataset_dict.json +1 -0
- hf_data/dev/data-00000-of-00001.arrow +3 -0
- hf_data/dev/dataset_info.json +53 -0
- hf_data/dev/state.json +13 -0
- hf_data/test_msa/data-00000-of-00001.arrow +3 -0
- hf_data/test_msa/dataset_info.json +53 -0
- hf_data/test_msa/state.json +13 -0
- hf_data/test_spoken/data-00000-of-00001.arrow +3 -0
- hf_data/test_spoken/dataset_info.json +53 -0
- hf_data/test_spoken/state.json +13 -0
- hf_data/train/data-00000-of-00001.arrow +3 -0
- hf_data/train/dataset_info.json +53 -0
- hf_data/train/state.json +13 -0
- iaa_A.jsonl +0 -0
- iaa_B.jsonl +0 -0
- label_mapping.json +56 -0
- unique_sentences.jsonl +0 -0
    	
        LICENSE
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            CC-BY-4.0
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        README.md
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            # Spoken-Arabic Named-Entity Dataset (Levantine NER v1.0)
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            A curated corpus of Levantine-Arabic sentences annotated for Named Entities, plus parallel dual-annotator files for assessing annotation noise.  
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            Ideal for fine-tuning Arabic-BERT–style models on noisy, spoken data and testing cross-register robustness.
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             | 
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            ---
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             | 
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            ## 1 Corpus snapshot
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            | statistic                              | value |
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            |----------------------------------------|-------|
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            | Sentences (unique set)                 | **23 422** |
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            | Sentences incl. 2nd annotator (A + B)  | **29 228** |
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            | Tokens (approx.)                       | ~290 k |
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            | Annotated entity spans                 | **17 589** |
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            | Avg. entities ∕ sentence               | 0.75 |
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            | Annotators                             | Arzy · Rawan · Reem · Sabil · Wiam · Amir |
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            | Rounds                                 | `round1` – `round5` (natural speech) + `round6` (synthetic news/MSA) |
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            | File format                            | JSON Lines (UTF-8) |
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             | 
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            ### Label inventory
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            | label  | description             | count |
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            |--------|-------------------------|------:|
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            | `GPE`  | geopolitical entity     | 4 601 |
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            | `PER`  | person                  | 3 628 |
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            | `ORG`  | organisation            | 1 426 |
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            | `MISC` | misc. named item        | 1 301 |
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            | `FAC`  | facility                |   947 |
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            | `TIMEX`| temporal expression     |   926 |
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            | `DUC`  | product/brand           |   711 |
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            | `EVE`  | event                   |   487 |
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            | `LOC`  | (non-GPE) location      |   467 |
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            | `ANG`  | angle/measure           |   322 |
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            | `WOA`  | work of art             |   292 |
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            | `TTL`  | title/honorific         |   227 |
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             | 
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            ---
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            ## 2 File list
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            | file | lines | purpose |
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            |------|------:|---------|
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            | **`unique_sentences.jsonl`** | 23 422 | canonical training/dev/test pool (one Levantine sentence per line) |
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            | **`iaa_A.jsonl`** | 5 806 | first annotator in each inter-annotator pair (not in `unique`) |
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            | **`iaa_B.jsonl`** | 5 806 | second annotator for the same sentences (aligned 1-to-1 with `iaa_A`) |
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            | `sentences.parquet` / `spans.parquet` | 52 274 / 17 589 | columnar versions for quick Pandas analysis (optional) |
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            ### Record schema (`unique_sentences.jsonl`)
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            ```jsonc
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            {
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              "doc_id"    : 137,
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              "doc_name"  : "22صدى-الصوت22",
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              "sent_id"   : 11,
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              "orig_ID"   : "29891",
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              "round"     : "round3",            // round1-5 natural, round6 synthetic
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              "annotator" : "Rawan",
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              "text"      : "جيب جوال أو أي اشي ضو هيك",
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              "source_type": "social_videos",
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              "spans": [
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                { "start": 4, "end": 8, "label": "DUC" }
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              ],
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              // only for round6
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              "msa": {
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                "text"  : "<parallel MSA sentence>",
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                "spans" : [{ "start": 5, "end": 16, "label": "LOC" }]
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              },
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              // provenance (optional)
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              "url"  : "https://…",
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              "date" : "2019-05-02 18:30:44"
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            }
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        dataset_card.yaml
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            ---
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            pretty_name: ShamNER
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            license: cc-by-4.0
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            language:
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              - ar
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            annotations_creators:
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              - expert-annotated
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            task_categories:
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              - token-classification
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            task_ids:
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              - named-entity-recognition
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            multilinguality: monolingual
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            ---
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        hf_data/dataset_dict.json
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            {"splits": ["train", "dev", "test_spoken", "test_msa"]}
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        hf_data/dev/data-00000-of-00001.arrow
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            size 1026848
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        hf_data/dev/dataset_info.json
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        hf_data/test_msa/data-00000-of-00001.arrow
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