metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
languages:
  - catalan
licenses:
  - cc-by-sa-4.0
multilinguality:
  - monolingual
pretty_name: VilaQuAD
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - question-answering
task_ids:
  - extractive-qa

VilaQuAD, An extractive QA dataset for catalan, from Vilaweb newswire text

Dataset Description

Paper: Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan
Point of Contact: Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es) and Carme Armentano-Oller (carme.armentano@bsc.es)

Dataset Summary

This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).

VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under CC-by-nc-sa-nd licence.

This dataset can be used to build extractive-QA and Language Models.

Supported Tasks and Leaderboards

Extractive-QA, Language Model

Languages

CA - Catalan

Dataset Structure

Data Instances

{
  "data": [
    {
      "title": "Com celebrar el Cap d'Any 2020? Deu propostes per a acomiadar-se del 2019",
      "paragraphs": [
        {
          "context": "Hi ha moltes propostes per a acomiadar-se d'aquest 2019. Els uns es queden a casa, els altres volen anar lluny o sortir al teatre. També s'organitzen festes o festivals a l'engròs, fins i tot hi ha propostes diürnes. Tot és possible per Cap d'Any. Encara no sabeu com celebrar l'entrada el 2020? Us oferim una llista amb deu propostes variades arreu dels Països Catalans: Festivern El Festivern enguany celebra quinze anys.",
          "qas": [
            {
              "answers": [
                {
                  "text": "festes o festivals",
                  "answer_start": 150
                }
              ],
              "id": "P_23_C_23_Q2",
              "question": "Què s'organitza a l'engròs per acomiadar el 2019?"
            },
            ...
          ]
        }
      ]
    }, 
    ...
   ]
}

Data Fields

Follows Rajpurkar, Pranav et al., 2016 for squad v1 datasets.

Data Splits

train.json: 1295 contexts, 3882 questions
dev.json: 400 contexts, 1200 questions
test.json: 400 contexts, 1200 questions

Dataset Creation

Methodology

From a the online edition of the catalan newspaper Vilaweb (https://www.vilaweb.cat), 2095 articles were randomnly selected. These headlines were also used to create a Textual Entailment dataset. For the extractive QA dataset, creation of between 1 and 5 questions for each news context was commissioned, 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)), http://arxiv.org/abs/1606.05250. In total, 6282 pairs of a question and an extracted fragment that contains the answer were created.

Curation Rationale

For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines. We also created another QA dataset with wikipedia to ensure thematic and stylistic variety.

Source Data

https://www.vilaweb.cat/

Initial Data Collection and Normalization

The source data are scraped articles from archives of Catalan newspaper website Vilaweb.

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

We comissioned 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

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es) and Carme Armentano-Oller (carme.armentano@bsc.es)

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

Funding

This work was funded by the Catalan Ministry of the Vice-presidency, Digital Policies and Territory within the framework of the Aina project.