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  ---
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-
 
 
 
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  languages:
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-
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- - ca
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-
 
 
 
 
 
 
 
 
 
 
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  ---
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  # VilaQuAD, An extractive QA dataset for catalan, from Vilaweb newswire text
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- ## BibTeX citation
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-
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- If you use any of these resources (datasets or models) in your work, please cite our latest paper:
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-
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- ```bibtex
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-
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- @inproceedings{armengol-estape-etal-2021-multilingual,
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-
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- title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
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-
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- author = "Armengol-Estap{\'e}, Jordi and
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-
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- Carrino, Casimiro Pio and
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-
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- Rodriguez-Penagos, Carlos and
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-
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- de Gibert Bonet, Ona and
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-
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- Armentano-Oller, Carme and
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-
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- Gonzalez-Agirre, Aitor and
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-
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- Melero, Maite and
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-
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- Villegas, Marta",
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-
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- booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
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-
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- month = aug,
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- year = "2021",
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- address = "Online",
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- publisher = "Association for Computational Linguistics",
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- url = "https://aclanthology.org/2021.findings-acl.437",
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- doi = "10.18653/v1/2021.findings-acl.437",
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- pages = "4933--4946",
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-
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- }
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-
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- ```
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-
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- ## Digital Object Identifier (DOI) and access to dataset files
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-
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- https://doi.org/10.5281/zenodo.4562337
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- ## Introduction
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- This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
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- VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under CC-by-nc-sa-nd (https://creativecommons.org/licenses/by-nc-nd/3.0/deed.ca) licence.
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  This dataset can be used to build extractive-QA and Language Models.
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  ### Supported Tasks and Leaderboards
@@ -71,28 +44,14 @@ Extractive-QA, Language Model
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  ### Languages
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- CA- Catalan
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-
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- ### Directory structure
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-
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- * README.md
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- * dev.json
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- * test.json
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- * train.json
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- * vilaquad.py
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  ## Dataset Structure
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  ### Data Instances
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- Three json files
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-
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- ### Data Fields
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-
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- Follows ((Rajpurkar, Pranav et al., 2016) for squad v1 datasets. (see below for full reference)
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-
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- ### Example:
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  <pre>
 
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  {
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  "data": [
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  {
@@ -101,7 +60,6 @@ Follows ((Rajpurkar, Pranav et al., 2016) for squad v1 datasets. (see below for
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  {
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  "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.",
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  "qas": [
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-
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  {
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  "answers": [
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  {
@@ -122,58 +80,23 @@ Follows ((Rajpurkar, Pranav et al., 2016) for squad v1 datasets. (see below for
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  }
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  </pre>
 
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- ### Data Splits
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-
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- train.json: 1295 contexts, 3882 questions
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- dev.json: 400 contexts, 1200 questions
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- test.json: 400 contexts, 1200 questions
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-
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- ## Content analysis
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-
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- ### Number of articles, paragraphs and questions
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-
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- * Number of contexts: 2095
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- * Number of questions: 6282
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- * Questions/context: 2.99
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- * Number of sentences in contexts: 11901
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- * Sentences/context: 5.6
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-
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- ### Number of tokens
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-
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- * tokens in context: 422477
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- * tokens/context 201.66
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- * tokens in questons: 65849
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- * tokens/questions: 10.48
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- * tokens in answers: 27716
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- * tokens/answers: 4.41
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-
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- ### Question type
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- | Question | Count | % |
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- |--------|-----|------|
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- | què | 1698 | 27.03 % |
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- | qui | 1161 | 18.48 % |
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- | com | 574 | 9.14 % |
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- | quan | 468 | 7.45 % |
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- | on | 559 | 8.9 % |
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- | quant | 601 | 9.57 % |
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- | quin | 1301 | 20.87 % |
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- | no question mark | 0 | 0.0 % |
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- ### Question-answer relationships
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- From 100 randomly selected samples:
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- * Lexical variation: 32.0%
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- * World knowledge: 16.0%
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- * Syntactic variation: 22.0%
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- * Multiple sentence: 16.0%
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174
  ## Dataset Creation
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176
  ### Methodology
 
177
  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.
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  ### Curation Rationale
@@ -186,7 +109,7 @@ For compatibility with similar datasets in other languages, we followed as close
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  #### Initial Data Collection and Normalization
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- The source data are scraped articles from archives of Catalan newspaper website Vilaweb (https://www.vilaweb.cat).
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  #### Who are the source language producers?
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@@ -196,16 +119,12 @@ The source data are scraped articles from archives of Catalan newspaper website
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  #### Annotation process
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- 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)), http://arxiv.org/abs/1606.05250.
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  #### Who are the annotators?
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  Annotation was commissioned to an specialized company that hired a team of native language speakers.
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- ### Dataset Curators
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-
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- Carlos Rodríguez and Carme Armentano, from BSC-CNS
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-
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  ### Personal and Sensitive Information
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  No personal or sensitive information included.
@@ -224,13 +143,43 @@ No personal or sensitive information included.
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  [More Information Needed]
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- ## Contact
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  Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected])
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- ## License
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- <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>.
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  ---
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+ annotations_creators:
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+ - expert-generated
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+ language_creators:
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+ - found
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  languages:
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+ - catalan
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+ licenses:
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+ - cc-by-sa-4.0
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+ multilinguality:
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+ - monolingual
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+ pretty_name: vilaquad
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+ size_categories:
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+ - unknown
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+ source_datasets: []
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+ task_categories:
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+ - question-answering
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+ task_ids:
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+ - extractive-qa
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  ---
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  # VilaQuAD, An extractive QA dataset for catalan, from Vilaweb newswire text
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+ ## Dataset Description
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+ - **Paper:** [Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan](https://arxiv.org/abs/2107.07903)
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+ - **Point of Contact:** Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected])
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+ ### Dataset Summary
 
 
 
 
 
 
 
 
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+ This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
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+ VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under [CC-by-nc-sa-nd](https://creativecommons.org/licenses/by-nc-nd/3.0/deed.ca) licence.
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  This dataset can be used to build extractive-QA and Language Models.
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  ### Supported Tasks and Leaderboards
 
44
 
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  ### Languages
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+ CA - Catalan
 
 
 
 
 
 
 
 
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  ## Dataset Structure
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  ### Data Instances
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  <pre>
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+
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  {
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  "data": [
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  {
 
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  {
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  "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.",
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  "qas": [
 
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  {
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  "answers": [
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  {
 
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  }
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  </pre>
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+ ### Data Fields
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+ Follows [Rajpurkar, Pranav et al., 2016](http://arxiv.org/abs/1606.05250) for squad v1 datasets.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ### Data Splits
 
 
 
 
 
 
 
 
 
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+ - train.json: 1295 contexts, 3882 questions
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+ - dev.json: 400 contexts, 1200 questions
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+ - test.json: 400 contexts, 1200 questions
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  ## Dataset Creation
97
 
98
  ### Methodology
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+
100
  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.
101
 
102
  ### Curation Rationale
 
109
 
110
  #### Initial Data Collection and Normalization
111
 
112
+ The source data are scraped articles from archives of Catalan newspaper website [Vilaweb](https://www.vilaweb.cat).
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114
  #### Who are the source language producers?
115
 
 
119
 
120
  #### Annotation process
121
 
122
+ 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)](http://arxiv.org/abs/1606.05250)).
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124
  #### Who are the annotators?
125
 
126
  Annotation was commissioned to an specialized company that hired a team of native language speakers.
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  ### Personal and Sensitive Information
129
 
130
  No personal or sensitive information included.
 
143
 
144
  [More Information Needed]
145
 
146
+ ## Additional Information
147
 
148
+ ### Dataset Curators
149
 
150
  Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected])
151
 
152
+ ### Licensing Information
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+
154
+ 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>.
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+
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+ ### Citation Information
157
+
158
+
159
 
160
+ ```
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+
162
+ @inproceedings{armengol-estape-etal-2021-multilingual,
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+ title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
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+ author = "Armengol-Estap{\'e}, Jordi and
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+ Carrino, Casimiro Pio and
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+ Rodriguez-Penagos, Carlos and
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+ de Gibert Bonet, Ona and
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+ Armentano-Oller, Carme and
169
+ Gonzalez-Agirre, Aitor and
170
+ Melero, Maite and
171
+ Villegas, Marta",
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+ booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
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+ month = aug,
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+ year = "2021",
175
+ address = "Online",
176
+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2021.findings-acl.437",
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+ doi = "10.18653/v1/2021.findings-acl.437",
179
+ pages = "4933--4946",
180
+ }
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+
182
+ ```
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+ [DOI](https://doi.org/10.5281/zenodo.4562337)
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