--- annotations_creators: - expert-generated language_creators: - found language: - es license: - cc-by-sa-4.0 multilinguality: - monolingual pretty_name: Spanish Question Answering Corpus (SQAC) source_datasets: - original task_categories: - question-answering task_ids: - extractive-qa --- # SQAC (Spanish Question-Answering Corpus) ## Dataset Description SQAC is an extractive QA dataset for the Spanish language. - **Paper:** [MarIA: Spanish Language Models](https://upcommons.upc.edu/bitstream/handle/2117/367156/6405-5863-1-PB%20%281%29.pdf?sequence=1) - **Point of Contact:** encargo-pln-life@bsc.es ### Dataset Summary Contains 6,247 contexts and 18,817 questions with their respective answers, 1 to 5 for each fragment. The sources of the contexts are: * Encyclopedic articles from the [Spanish Wikipedia](https://es.wikipedia.org/), used under [CC-by-sa licence](https://creativecommons.org/licenses/by-sa/3.0/legalcode). * News articles from [Wikinews](https://es.wikinews.org/), used under [CC-by licence](https://creativecommons.org/licenses/by/2.5/). * Newswire and literature text from the [AnCora corpus](http://clic.ub.edu/corpus/en), used under [CC-by licence](https://creativecommons.org/licenses/by/4.0/legalcode). ### Supported Tasks Extractive-QA ### Languages - Spanish (es) ### Directory Structure - README.md - SQAC.py - dev.json - test.json - train.json ## Dataset Structure ### Data Instances 
{
	'id': '6cf3dcd6-b5a3-4516-8f9e-c5c1c6b66628', 
	'title': 'Historia de Japón', 
	'context': 'La historia de Japón (日本の歴史 o 日本史, Nihon no rekishi / Nihonshi?) es la sucesión de hechos acontecidos dentro del archipiélago japonés. Algunos de estos hechos aparecen aislados e influenciados por la naturaleza geográfica de Japón como nación insular, en tanto que otra serie de hechos, obedece a influencias foráneas como en el caso del Imperio chino, el cual definió su idioma, su escritura y, también, su cultura política. Asimismo, otra de las influencias foráneas fue la de origen occidental, lo que convirtió al país en una nación industrial, ejerciendo con ello una esfera de influencia y una expansión territorial sobre el área del Pacífico. No obstante, dicho expansionismo se detuvo tras la Segunda Guerra Mundial y el país se posicionó en un esquema de nación industrial con vínculos a su tradición cultural.', 
	'question': '¿Qué influencia convirtió Japón en una nación industrial?', 
	'answers': {
		'text': ['la de origen occidental'], 
		'answer_start': [473]
	}
}
### Data Fields 
{
  id: str
  title: str
  context: str
  question: str
  answers: {
    answer_start: [int]
    text: [str]
  }
}
### Data Splits | Split | Size | | ------------- | ------------- | | `train` | 15,036 | | `dev` | 1,864 | | `test` | 1.910 | ## Content analysis ### Number of articles, paragraphs and questions * Number of articles: 3,834 * Number of contexts: 6,247 * Number of questions: 18,817 * Number of sentences: 48,026 * Questions/Context ratio: 3.01 * Sentences/Context ratio: 7.70 ### Number of tokens * Total tokens in context: 1,561,616 * Average tokens/context: 250 * Total tokens in questions: 203,235 * Average tokens/question: 10.80 * Total tokens in answers: 90,307 * Average tokens/answer: 4.80 ### Lexical variation 46.38% of the words in the Question can be found in the Context. ### Question type | Question | Count | % | |----------|-------:|---:| | qué | 6,381 | 33.91 % | | quién/es | 2,952 | 15.69 % | | cuál/es | 2,034 | 10.81 % | | cómo | 1,949 | 10.36 % | | dónde | 1,856 | 9.86 % | | cuándo | 1,639 | 8.71 % | | cuánto | 1,311 | 6.97 % | | cuántos | 495 |2.63 % | | adónde | 100 | 0.53 % | | cuánta | 49 | 0.26 % | | no question mark | 43 | 0.23 % | | cuántas | 19 | 0.10 % | ## Dataset Creation ### Curation Rationale For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines. ### Source Data #### Initial Data Collection and Normalization The source data are scraped articles from Wikinews, the Spanish Wikipedia and the AnCora corpus. - [Spanish Wikipedia](https://es.wikipedia.org) - [Spanish Wikinews](https://es.wikinews.org/) - [AnCora corpus](http://clic.ub.edu/corpus/en) #### Who are the source language producers? Contributors to the aforementioned sites. ### 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.)](http://arxiv.org/abs/1606.05250). #### Who are the annotators? Native language speakers. ### Personal and Sensitive Information No personal or sensitive information included. ## Considerations for Using the Data ### Social Impact of Dataset This corpus contributes to the development of language models in Spanish. ### Discussion of Biases No postprocessing steps were applied to mitigate potential social biases. ## Additional Information ### Dataset Curators - Carme Armentano Oller (carme.armentano@bsc.es) - Carlos Rodríguez Penagos (carlos.rodriguez1@bsc.es) ### Citation Information ``` @article{maria, author = {Asier Gutiérrez-Fandiño and Jordi Armengol-Estapé and Marc Pàmies and Joan Llop-Palao and Joaquin Silveira-Ocampo and Casimiro Pio Carrino and Carme Armentano-Oller and Carlos Rodriguez-Penagos and Aitor Gonzalez-Agirre and Marta Villegas}, title = {MarIA: Spanish Language Models}, journal = {Procesamiento del Lenguaje Natural}, volume = {68}, number = {0}, year = {2022}, issn = {1989-7553}, url = {http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6405}, pages = {39--60} } ``` ### Contact Information For further information, send an email to encargo-pln-life@bsc.es. ### Funding This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL. ### Licensing Information Attribution-ShareAlike 4.0 International License
This work is licensed under a Attribution-ShareAlike 4.0 International License.