ViquiQuAD: An Extractive QA Dataset for Catalan from Wikipedia

Dataset Summary

ViquiQuAD is an extractive Question Answering dataset for Catalan, built from the Catalan Wikipedia (Viquipèdia).

• 3,111 contexts extracted from 597 high-quality, original (non-translated) articles.
• For each context, 1 to 5 questions were created with their corresponding answers.
• Total: 15,153 question–answer pairs.

This dataset can be used to fine-tune and evaluate extractive QA models and other Catalan language models.

Sources: Catalan Wikipedia (licensed under CC BY-SA 4.0).

Supported Tasks and Leaderboards

• Extractive Question Answering
• Evaluation for Catalan Language Models

Languages

• Catalan (ca-ES)

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Dataset Structure

Data Instances

{
  "id": "P_66_C_391_Q1",
  "title": "Xavier Miserachs i Ribalta",
  "context": "En aquesta època es va consolidar el concepte modern del reportatge fotogràfic...",
  "question": "De què es diferenciava el reportatge fotogràfic?",
  "answers": [{
    "text": "del fotoperiodisme[n. 2] i de la fotografia documental",
    "answer_start": 92
  }]
}

Data Fields

Following SQuAD v1.0:

• id (str): Unique identifier.

• title (str): Title of the Wikipedia article.

• context (str): Text passage from Wikipedia.

• question (str): Question posed about the context.

• answers (list of dicts): Each answer contains:

  • text (str): Answer span from the context.
  • answer_start (int): Character offset of the answer.

Data Splits

• train: 11,259 examples
• dev: 1,493 examples
• test: 1,428 examples

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Dataset Creation

Curation Rationale

Designed to provide a high-quality resource for Catalan, a low-resource language, to train and evaluate extractive QA systems.

Source Data

• Collection: Articles scraped from the Catalan Wikipedia.
• Selection: 597 high-quality, non-translated articles.
• Contexts: 3,111 contexts (5–8 sentences each) extracted.
• Questions: 1–5 questions created per context → 15,153 QA pairs.
• Guidelines: Adapted from SQuAD 1.0.

Source Language Producers

Volunteer contributors to Catalan Wikipedia.

Annotations

• Process: Professional annotators created questions and answers following adapted SQuAD guidelines.
• Annotators: Commissioned to a specialized company with native Catalan speakers.

Personal and Sensitive Information

No personal or sensitive information is included.

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Considerations for Using the Data

Social Impact

Supports the development of NLP for Catalan, reducing the resource gap for minority languages.

Discussion of Biases

• May inherit coverage biases present in Wikipedia.
• Articles selected are high-quality but do not fully represent all domains of Catalan usage.

Other Known Limitations

• Limited domain (Wikipedia) may reduce generalizability.

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Additional Information

Dataset Curators

• Text Mining Unit (TeMU), Barcelona Supercomputing Center (BSC)

  • Contact: bsc-temu@bsc.es

Funding

Funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya, within the framework of Projecte AINA.

Licensing Information

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Information

@inproceedings{armengol-estape-etal-2021-multilingual,
    title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
    author = "Armengol-Estap{\'e}, Jordi  and
      Carrino, Casimiro Pio  and
      Rodriguez-Penagos, Carlos  and
      de Gibert Bonet, Ona  and
      Armentano-Oller, Carme  and
      Gonzalez-Agirre, Aitor  and
      Melero, Maite  and
      Villegas, Marta",
    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.findings-acl.437",
    doi = "10.18653/v1/2021.findings-acl.437",
    pages = "4933--4946",
}

DOI: 10.5281/zenodo.4562344

Contributions

N/A