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metadata
annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - ca
license:
  - cc-by-sa-4.0
multilinguality:
  - monolingual
pretty_name: ViquiQuAD
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - question-answering
task_ids:
  - extractive-qa

ViquiQuAD, An extractive QA dataset for Catalan, from the Wikipedia

Table of Contents

Dataset Description

Dataset Summary

ViquiQuAD, An extractive QA dataset for Catalan, from the Wikipedia.

This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations) articles in the Catalan Wikipedia "Viquipèdia", and 1 to 5 questions with their answer for each fragment.

Viquipedia articles are used under CC-by-sa licence.

This dataset can be used to fine-tune and evaluate extractive-QA and Language Models.

Supported Tasks and Leaderboards

Extractive-QA, Language Model

Languages

The dataset is in Catalan (ca-ES).

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, diferenciat del fotoperiodisme[n. 2] i de la fotografia documental,[n. 3] pel que fa a l'abast i el concepte. El reportatge fotogràfic implica més la idea de relat: un treball que vol més dedicació de temps, un esforç d'interpretació d'una situació i que culmina en un conjunt d'imatges. Això implica, d'una banda, la reivindicació del fotògraf per opinar, fet que li atorgarà estatus d'autor; l'autor proposa, doncs, una interpretació pròpia de la realitat. D'altra banda, el consens que s'estableix entre la majoria de fotògrafs és que el vehicle natural de la imatge fotogràfica és la pàgina impresa. Això suposà que revistes com Life, Paris-Match, Stern o Época assolissin la màxima esplendor en aquest període.",
  'question': 'De què es diferenciava el reportatge fotogràfic?',
  'answers': [{
    'text': 'del fotoperiodisme[n. 2] i de la fotografia documental',
    'answer_start': 92
  }]
}

Data Fields

Follows Rajpurkar, Pranav et al. (2016) for SQuAD v1 datasets.

  • id (str): Unique ID assigned to the question.
  • title (str): Title of the Wikipedia article.
  • context (str): Wikipedia section text.
  • question (str): Question.
  • answers (list): List of answers to the question, each containing:
    • text (str): Span text answering to the question.
    • answer_start Starting offset of the span text answering to the question.

Data Splits

  • train: 11259 examples
  • developement: 1493 examples
  • test: 1428 examples

Dataset Creation

Curation Rationale

We hope this dataset contributes to the development of language models in Catalan, a low-resource language.

Source Data

Initial Data Collection and Normalization

The source data are scraped articles from the Catalan wikipedia site.

From a set of high quality, non-translation, articles inCA the Catalan Wikipedia, 597 were randomly chosen, and from them 3111, 5-8 sentence contexts were extracted. We commissioned creation of between 1 and 5 questions for each context, following an adaptation of the guidelines from SQuAD 1.0 (Rajpurkar, Pranav et al. (2016)). In total, 15153 pairs of a question and an extracted fragment that contains the answer were created.

For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.

Who are the source language producers?

Volunteers who collaborate with Catalan Wikipedia.

Annotations

Annotation process

We commissioned the creation of 1 to 5 questions for each context, following an adaptation of the guidelines from SQuAD 1.0 (Rajpurkar, Pranav et al. (2016)).

Who are the annotators?

Annotation was commissioned to an specialized company that hired a team of native language speakers.

Personal and Sensitive Information

No personal or sensitive information included.

Considerations for Using the Data

Social Impact of Dataset

We hope this dataset contributes to the development of language models in Catalan, a low-resource language.

Discussion of Biases

[N/A]

Other Known Limitations

[N/A]

Additional Information

Dataset Curators

Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)

This work was 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 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

Contributions

[N/A]