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Datasets:
HebArabNlpProject
/
ShamNER

Tasks:
Token Classification
Modalities:
Tabular
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
Arabic
Size:
10K - 100K
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
xet
Community
1
ShamNER
File size: 2,798 Bytes 
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# Spoken-Arabic Named-Entity Dataset (Levantine NER v1.0)

A curated corpus of Levantine-Arabic sentences annotated for Named Entities, plus parallel dual-annotator files for assessing annotation noise.  
Ideal for fine-tuning Arabic-BERT–style models on noisy, spoken data and testing cross-register robustness.

---

## 1 Corpus snapshot

| statistic                              | value |
|----------------------------------------|-------|
| Sentences (unique set)                 | **23 422** |
| Sentences incl. 2nd annotator (A + B)  | **29 228** |
| Tokens (approx.)                       | ~290 k |
| Annotated entity spans                 | **17 589** |
| Avg. entities ∕ sentence               | 0.75 |
| Annotators                             | Arzy · Rawan · Reem · Sabil · Wiam · Amir |
| Rounds                                 | `round1` – `round5` (natural speech) + `round6` (synthetic news/MSA) |
| File format                            | JSON Lines (UTF-8) |

### Label inventory

| label  | description             | count |
|--------|-------------------------|------:|
| `GPE`  | geopolitical entity     | 4 601 |
| `PER`  | person                  | 3 628 |
| `ORG`  | organisation            | 1 426 |
| `MISC` | misc. named item        | 1 301 |
| `FAC`  | facility                |   947 |
| `TIMEX`| temporal expression     |   926 |
| `DUC`  | product/brand           |   711 |
| `EVE`  | event                   |   487 |
| `LOC`  | (non-GPE) location      |   467 |
| `ANG`  | angle/measure           |   322 |
| `WOA`  | work of art             |   292 |
| `TTL`  | title/honorific         |   227 |

---

## 2 File list

| file | lines | purpose |
|------|------:|---------|
| **`unique_sentences.jsonl`** | 23 422 | canonical training/dev/test pool (one Levantine sentence per line) |
| **`iaa_A.jsonl`** | 5 806 | first annotator in each inter-annotator pair (not in `unique`) |
| **`iaa_B.jsonl`** | 5 806 | second annotator for the same sentences (aligned 1-to-1 with `iaa_A`) |
| `sentences.parquet` / `spans.parquet` | 52 274 / 17 589 | columnar versions for quick Pandas analysis (optional) |

### Record schema (`unique_sentences.jsonl`)

```jsonc
{
  "doc_id"    : 137,
  "doc_name"  : "22صدى-الصوت22",
  "sent_id"   : 11,
  "orig_ID"   : "29891",
  "round"     : "round3",            // round1-5 natural, round6 synthetic
  "annotator" : "Rawan",
  "text"      : "جيب جوال أو أي اشي ضو هيك",
  "source_type": "social_videos",
  "spans": [
    { "start": 4, "end": 8, "label": "DUC" }
  ],

  // only for round6
  "msa": {
    "text"  : "<parallel MSA sentence>",
    "spans" : [{ "start": 5, "end": 16, "label": "LOC" }]
  },

  // provenance (optional)
  "url"  : "https://…",
  "date" : "2019-05-02 18:30:44"
}