ELNER-DZ: Algerian Arabic Dataset for Named Entity Recognition and Entity Linking

📌 Official DOI:
🤗 Also available on Hugging Face
📥 Download Dataset (.rar from Zenodo)

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This dataset, titled ELNER-DZ, was created by Bouguettoucha Hadjer Hanine and Djouablia Ilhem as part of our Master’s thesis. It is the first large-scale dataset designed for Named Entity Recognition (NER) and Entity Linking (EL) in Algerian Arabic Dialect (Darija), including both Arabic script and Arabizi (Latin-script).

This dataset contains over 2 million dialectal sentences labeled with more than 1.9 million named entities and linked to Wikidata QIDs.

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🧾 Dataset Summary

• Name: ELNER-DZ
• Languages: Arabic (ar for MSA, arq for dialectal), Arabizi (Latin), French (fr), English (en)
• Script: Arabic and Latin (Arabizi)
• Format: JSON (compressed in data.rar)
• Annotations:
  • Named Entity spans (start, end)
  • NER labels (PER, LOC, ORG, etc.)
  • Normalized forms
  • Wikidata QIDs

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📁 File Structure

• data/data.rar — Compressed archive containing data.json
• examples/loading_example.py — Script to extract and load the dataset
• LICENSE — CC-BY-4.0
• dataset_card.md — Hugging Face dataset summary

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✨ Example Format

{
  "id": 188,
  "text": "3reft wa7ed lperson khadem f Yassir",
  "entities": [
    {
      "start": 29,
      "end": 35,
      "label": "ORG",
      "wikidata_id": "Q117156470",
      "normalized": "Yassir"
    }
  ]
}

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🏷️ Entity Types

• PER: Person
• LOC: Location
• ORG: Organization
• PROD: Product
• LAW: Legal texts or rules
• LANG: Language
• EVENT: Events
• DATE: Temporal expressions
• NORP: Nationality/Religious/Political groups
• SPORT: Sports & Competitions
• SYMPTOM, DISEASE: Medical categories
• MISC: Miscellaneous

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🧪 Tasks Supported

• Named Entity Recognition (NER)
• Entity Linking (EL) with Wikidata
• Dialectal NLP in Algerian Arabic
• Code-switching and multiscript modeling
• Low-resource transfer learning

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🧰 How to Use

▶️ Requirements

pip install datasets rarfile
sudo apt-get install unrar    # For Linux

▶️ Run the loading script

python examples/loading_example.py

Or manually extract and load:

import rarfile
rf = rarfile.RarFile("data/data.rar")
rf.extractall("data/")

from datasets import load_dataset
dataset = load_dataset("json", data_files="data/data.json", split="train")
print(dataset[0])

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🔍 Dataset Details

• Source: Social media, dialogues, e-commerce, Wikidata SPARQL

• Annotation:

  • Semi-automated and rule-based extraction
  • Manual normalization of entity surface forms
  • Wikidata QID linking via SPARQL and fallback search

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👩‍💻 Authors

• Bouguettoucha Hadjer Hanine
• Djouablia Ilhem

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📄 License

This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

🔗 View Full License

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📚 Citation

@dataset{bouguettoucha_djouablia_2025,
  author       = {Bouguettoucha, Hadjer Hanine and Djouablia, Ilhem},
  title        = {ELNER-DZ: A Dataset for Named Entity Recognition and Linking in Algerian Arabic},
  year         = 2025,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.15798592},
  url          = {https://doi.org/10.5281/zenodo.15798592}
}