Update README.md

README.md

@@ -10,8 +10,6 @@ license:
 multilinguality:
 - monolingual
 pretty_name: Spanish Question Answering Corpus (SQAC)
-size_categories:
-- unknown
 source_datasets:
 - original
 task_categories:
@@ -21,39 +19,52 @@ task_ids:
 
 ---
 
-# SQAC (Spanish Question-Answering Corpus): An extractive QA dataset for the Spanish language
-
-## BibTeX  citation
-
-```bibtex
-@article{gutierrezfandino2022,
-	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}
-}
-```
-
-See the pre-print version of our paper for further details: https://arxiv.org/abs/2107.07253
-
-<!-- ## Digital Object Identifier (DOI) and access to dataset files --> 
-
-
-## Introduction
-
-This dataset contains 6,247 contexts and 18,817 questions with their answers, 1 to 5 for each fragment.
+# SQAC (Spanish Question-Answering Corpus)
+An extractive QA dataset for the Spanish language.
+
+## Table of Contents
+<details>
+<summary>Click to expand</summary>
+  
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Citation Information](#citation-information)
+  - Contact Information](#contact-information)
+  - [Funding](#funding)
+  - [Licensing Information](#licensing-information)
+  
+</details>
+
+## Dataset Description
+
+- **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:** [email protected]
+
+### Dataset Summary
+
+This dataset 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 [Wikipedia in Spanish](https://es.wikipedia.org/), used under [CC-by-sa licence](https://creativecommons.org/licenses/by-sa/3.0/legalcode). 
-* News from [Wikinews in Spanish](https://es.wikinews.org/), used under [CC-by licence](https://creativecommons.org/licenses/by/2.5/). 
-* Text from the Spanish corpus [AnCora](http://clic.ub.edu/corpus/en), which is a mix from diferent newswire and literature sources, used under [CC-by licence](https://creativecommons.org/licenses/by/4.0/legalcode). 
-
-This dataset can be used to build extractive-QA.
+* 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/). 
+* Text from the [AnCora corpus](http://clic.ub.edu/corpus/en), which is a mix from several newswire and literature sources, used under [CC-by licence](https://creativecommons.org/licenses/by/4.0/legalcode). 
 
 ### Supported Tasks and Leaderboards
 
@@ -61,66 +72,45 @@ Extractive-QA
 
 ### Languages
 
-ES - Spanish
-
-### Directory structure
-
-* README.md
-* dev.json
-* test.json
-* train.json
-* sqac.py
+- Spanish (es)
 
 ## Dataset Structure
 
 ### Data Instances
 
-JSON files
+<pre>
+{
+	'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]
+	}
+}
+</pre>
 
 ### Data Fields
 
-Follows (Rajpurkar, Pranav et al., 2016) for squad v1 datasets. (see below for full reference).
-We added a field "source" with the source of the context.
-
-### Example
-<pre>
 {
-  "data": [
-    {
-      "paragraphs": [
-        {
-          "context": "Al cogote, y fumando como una cafetera. Ah!, no era él, éramos todos nosotros. Luego llegó Billie Holiday. Bajo el epígrafe Arte, la noche temática, pasaron la vida de la única cantante del universo que no es su voz, sino su alma lo que se escucha cuando interpreta. Gata golpeada por el mundo, pateada, violada, enganchada a todos los paraísos artificiales del planeta, jamás encontró el Edén. El Edén lo encontramos nosotros cuando, al concluir la sesión de la tele, pusimos en la doméstica cadena de sonido el mítico Last Recording, su última grabación (marzo de 1959), con la orquesta de Ray Ellis y el piano de Hank Jones. Se estaba muriendo Lady Day, y no obstante, mientras moría, su alma cantaba, Baby, won't you please come home. O sea, niño, criatura, amor, vuelve, a casa por favor.",
-          "qas": [
-            {
-              "question": "¿Quién se incorporó a la reunión más adelante?",
-              "id": "c5429572-64b8-4c5d-9553-826f867b07be",
-              "answers": [
-                {
-                  "answer_start": 91,
-                  "text": "Billie Holiday"
-                }
-              ]
-            },
-            
-            ...
-            
-            ]
-        }
-      ],
-      "title": "P_129_20010702_&_P_154_20010102_&_P_108_20000301_c_&_P_108_20000601_d",
-      "source": "ancora"
-    },
-    ...
-  ]
+- `id`: str
+- `title`: str
+- `context`: str
+- `question`: str
+- `answers`: {
+		- `answer_start`: [int]
+		- `text`: [str]
+	}
 }
 
-</pre>
-
 ### Data Splits
 
-- train
-- development
-- test
+| Split | Size |
+| ------------- | ------------- |
+| `train`  | 15,036  |
+| `dev`  | 1,864  |
+| `test`  | 1.910  |
 
 ## Content analysis
 
@@ -129,24 +119,22 @@ We added a field "source" with the source of the context.
 * Number of articles: 3,834
 * Number of contexts: 6,247
 * Number of questions: 18,817
-* Questions/context: 3.01
 * Number of sentences: 48,026
-* Sentences/context: 7.70
+* Questions/Context ratio: 3.01
+* Sentences/Context ratio: 7.70
 
 ### Number of tokens
 
 * Total tokens in context: 1,561,616
-* Tokens/context 250.30
+* Average tokens/context: 250
 * Total tokens in questions: 203,235
-* Tokens in questions/questions: 10.80
-* Tokens in questions/tokens in context: 0.13
+* Average tokens/question: 10.80
 * Total tokens in answers: 90,307
-* Tokens in answers/answers: 4.80
-* Tokens in answers/tokens in context: 0.06
+* Average tokens/answer: 4.80
 
 ### Lexical variation
 
-46.38 of the words in the Question can be found in the Context.
+46.38 % of the words in the Question can be found in the Context.
 
 ### Question type 
 
@@ -165,47 +153,36 @@ We added a field "source" with the source of the context.
 | no question mark | 43 | 0.23 % |
 | cuántas | 19 | 0.10 % |
 
-
 ## Dataset Creation
 
-### Methodology
-
-6,247 contexts were randomly chosen from the three corpus described below. We commisioned the 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, 18,817 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.
+For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.
 
 ### Source Data
 
-- Spanish Wikipedia: https://es.wikipedia.org
-- Spanish Wikinews: https://es.wikinews.org/
-- AnCora corpus: http://clic.ub.edu/corpus/en
-
 #### Initial Data Collection and Normalization
 
-The source data are scraped articles from the Spanish Wikipedia site, Wikinews site and from AnCora corpus.
+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?
 
-[More Information Needed]
+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. “SQuAD: 100, 000+ Questions for Machine Comprehension of Text.” EMNLP (2016)](http://arxiv.org/abs/1606.05250).
-
+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.
 
-### Dataset Curators
-
-Carlos Rodríguez and Carme Armentano, from BSC-CNS.
-
 ### Personal and Sensitive Information
 
 No personal or sensitive information included.
@@ -214,23 +191,43 @@ No personal or sensitive information included.
 
 ### Social Impact of Dataset
 
-[More Information Needed]
+This corpus contributes to the development of language models in Spanish.
 
 ### Discussion of Biases
 
-[More Information Needed]
+No postprocessing steps were applied to mitigate potential social biases.
+
+## Additional Information
+
+### Dataset Curators
+
+- Carme Armentano-Oller ([email protected])
+- Carlos Rodríguez-Penagos ([email protected])
+
+### Citation Information
 
-### Other Known Limitations
+```
+@article{sqac,
+	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}
+}
+```
 
-[More Information Needed]
+### Contact Information
 
-## Contact
+For further information, send an email to [email protected].
 
-Carlos Rodríguez-Penagos or Carme Armentano-Oller ([email protected])
+### Funding
 
-## Funding
 This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL.
 
-## License
+### Licensing Information
 
-<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>.
+<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>.