Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
json
Sub-tasks:
extractive-qa
Languages:
Catalan
Size:
< 1K
ArXiv:
License:
| languages: | |
| - ca | |
| # ViquiQuAD, An extractive QA dataset for catalan, from the Wikipedia | |
| ## BibTeX citation | |
| If you use any of these resources (datasets or models) in your work, please cite our latest paper: | |
| ```bibtex | |
| @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", | |
| } | |
| ``` | |
| # Digital Object Identifier (DOI) and access to dataset files | |
| https://doi.org/10.5281/zenodo.4562345 | |
| ## Introduction | |
| This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations) articles in the Catalan Wikipedia "Viquipèdia" (ca.wikipedia.org), and 1 to 5 questions with their answer for each fragment. | |
| Viquipedia articles are used under [CC-by-sa] (https://creativecommons.org/licenses/by-sa/3.0/legalcode) 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) as presented in: | |
| Armengol-Estapé J., Carrino CP., Rodriguez-Penagos C., de Gibert Bonet O., Armentano-Oller C., Gonzalez-Agirre A., Melero M. and Villegas M.,Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan". Findings of ACL 2021 (ACL-IJCNLP 2021). | |
| ### Supported Tasks and Leaderboards | |
| Extractive-QA, Language Model | |
| ### Languages | |
| CA- Catalan | |
| ### Directory structure | |
| * README | |
| * dev.json | |
| * test.json | |
| * train.json | |
| * viquiquad.py | |
| ## Dataset Structure | |
| ### Data Instances | |
| json files | |
| ### Data Fields | |
| Follows ((Rajpurkar, Pranav et al., 2016) for squad v1 datasets. (see below for full reference) | |
| ### Example: | |
| <pre> | |
| { | |
| "data": [ | |
| { | |
| "title": "Frederick W. Mote", | |
| "paragraphs": [ | |
| { | |
| "context": "L'historiador Frederick W. Mote va escriure que l'ús del terme \\\\\\\\\\\\\\\\"classes socials\\\\\\\\\\\\\\\\" per a aquest sistema era enganyós i que la posició de les persones dins del sistema de quatre classes no era una indicació del seu poder social i riquesa reals, sinó que només implicava \\\\\\\\\\\\\\\\"graus de privilegi\\\\\\\\\\\\\\\\" als quals tenien dret institucionalment i legalment, de manera que la posició d'una persona dins de les classes no era una garantia de la seva posició, ja que hi havia xinesos rics i amb bona reputació social, però alhora hi havia menys mongols i semu rics que mongols i semu que vivien en la pobresa i eren maltractats.", | |
| "qas": [ | |
| { | |
| "answers": [ | |
| { | |
| "text": "Frederick W. Mote", | |
| "answer_start": 14 | |
| } | |
| ], | |
| "id": "5728848cff5b5019007da298", | |
| "question": "Qui creia que el sistema de classes socials de Yuan no s’hauria d’anomenar classes socials?" | |
| }, | |
| ... | |
| ] | |
| } | |
| ] | |
| }, | |
| ... | |
| ] | |
| } | |
| </pre> | |
| ### Data Splits | |
| train.development,test | |
| ## Content analysis | |
| ### Number of articles, paragraphs and questions | |
| * Number of articles: 597 | |
| * Number of contexts: 3111 | |
| * Number of questions: 15153 | |
| * Questions/context: 4.87 | |
| * Number of sentences in contexts: 15100 | |
| * Sentences/context: 4.85 | |
| ### Number of tokens | |
| * tokens in context: 469335 | |
| * tokens/context 150.86 | |
| * tokens in questions: 145249 | |
| * tokens/questions: 9.58 | |
| * tokens in answers: 63246 | |
| * tokens/answers: 4.17 | |
| ### Lexical variation | |
| After filtering (tokenization, stopwords, punctuation, case), 83,88% of the words in the question can be found in the Context | |
| ### Question type | |
| | Question | Count | % | | |
| |--------|-----|------| | |
| | què | 4220 | 27.85 % | | |
| | qui | 2239 | 14.78 % | | |
| | com | 1964 | 12.96 % | | |
| | quan | 1133 | 7.48 % | | |
| | on | 1580 | 10.43 % | | |
| | quant | 925 | 6.1 % | | |
| | quin | 3399 | 22.43 % | | |
| | no question mark | 21 | 0.14 % | | |
| ### Question-answer relationships | |
| From 100 randomly selected samples: | |
| * Lexical variation: 33.0% | |
| * World knowledge: 16.0% | |
| * Syntactic variation: 35.0% | |
| * Multiple sentence: 17.0% | |
| ## Dataset Creation | |
| ### Methodology | |
| From a set of high quality, non-translation, articles in the Catalan Wikipedia (ca.wikipedia.org), 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)], (http://arxiv.org/abs/1606.05250). In total, 15153 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. | |
| ### Source Data | |
| - https://ca.wikipedia.org | |
| #### Initial Data Collection and Normalization | |
| The source data are scraped articles from the Catalan wikipedia site (https://ca.wikipedia.org). | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### 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)), http://arxiv.org/abs/1606.05250. | |
| #### Who are the annotators? | |
| Native language speakers. | |
| ### Dataset Curators | |
| Carlos Rodríguez and Carme Armentano, from BSC-CNS | |
| ### 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] | |
| ## Contact | |
| Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es) and Carme Armentano-Oller (carme.armentano@bsc.es) | |
| ## License | |
| <a rel="license" href="https://creativecommons.org/licenses/by-sa/4.0/"><img alt="Attribution-ShareAlike 4.0 International License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by-sa/4.0/">Attribution-ShareAlike 4.0 International License</a>. | |