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 Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://zenodo.org/record/4562345#.YK41aqGxWUk
Paper: Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan
Point of Contact: Carlos Rodríguez-Penagos and Carme Armentano-Oller

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. It is part of the Catalan Language Understanding Benchmark (CLUB).

Supported Tasks and Leaderboards

Extractive-QA, Language Model

Languages

The dataset is in Catalan (ca-CA).

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 corpus contributes to the development of language models in Catalan, a low-resource language.

Source Data

Catalan Wikipedia

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 in 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. “SQuAD: 100, 000+ Questions for Machine Comprehension of Text.” EMNLP (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. “SQuAD: 100, 000+ Questions for Machine Comprehension of Text.” EMNLP (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