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README.md

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----
-annotations_creators:
-- expert-generated
-language_creators:
-- found
-language:
-- ca
-license:
-- cc-by-sa-4.0
-multilinguality:
-- monolingual
-pretty_name: ViquiQuAD
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- question-answering
-task_ids:
-- extractive-qa
----
-
-# ViquiQuAD, An extractive QA dataset for Catalan, from the Wikipedia
-
-## Table of Contents
-- [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)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** https://zenodo.org/record/4562345#.YK41aqGxWUk
-- **Paper:** [Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan](https://arxiv.org/abs/2107.07903)
-- **Point of Contact:** [Carlos Rodríguez-Penagos](mailto:[email protected]) and [Carme Armentano-Oller](mailto:[email protected])
-
-### Dataset Summary
-
-ViquiQuAD, An extractive QA dataset for Catalan, from the Wikipedia.
-
-This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations) articles in the Catalan Wikipedia "[Viquipèdia](https://ca.wikipedia.org/wiki/Portada)", 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. 
-
-### Supported Tasks and Leaderboards
-
-Extractive-QA, Language Model
-
-### Languages
-
-The dataset is in Catalan (`ca-CA`).
-
-## Dataset Structure
-
-### Data Instances
-
-```
-{
-  'id': 'P_66_C_391_Q1',
-  'title': 'Xavier Miserachs i Ribalta',
-  'context': "En aquesta època es va consolidar el concepte modern del reportatge fotogràfic, diferenciat del fotoperiodisme[n. 2] i de la fotografia documental,[n. 3] pel que fa a l'abast i el concepte. El reportatge fotogràfic implica més la idea de relat: un treball que vol més dedicació de temps, un esforç d'interpretació d'una situació i que culmina en un conjunt d'imatges. Això implica, d'una banda, la reivindicació del fotògraf per opinar, fet que li atorgarà estatus d'autor; l'autor proposa, doncs, una interpretació pròpia de la realitat. D'altra banda, el consens que s'estableix entre la majoria de fotògrafs és que el vehicle natural de la imatge fotogràfica és la pàgina impresa. Això suposà que revistes com Life, Paris-Match, Stern o Época assolissin la màxima esplendor en aquest període.",
-  'question': 'De què es diferenciava el reportatge fotogràfic?',
-  'answers': [{
-    'text': 'del fotoperiodisme[n. 2] i de la fotografia documental',
-    'answer_start': 92
-  }]
-}
-```
-
-### Data Fields
-
-Follows [Rajpurkar, Pranav et al. (2016)](http://arxiv.org/abs/1606.05250) for SQuAD v1 datasets.
-
-- `id` (str): Unique ID assigned to the question.
-- `title` (str): Title of the Wikipedia article.
-- `context` (str): Wikipedia section text.
-- `question` (str): Question.
-- `answers` (list): List of answers to the question, each containing:
-  - `text` (str): Span text answering to the question.
-  - `answer_start` Starting offset of the span text answering to the question.
-
-### Data Splits
-
-- train: 11259 examples
-- developement: 1493 examples
-- test: 1428 examples
-
-
-## Dataset Creation
-
-### Curation Rationale
-
-We hope this dataset contributes to the development of language models in Catalan, a low-resource language.
-
-### Source Data
-
-- [Catalan Wikipedia](https://ca.wikipedia.org)
-
-#### Initial Data Collection and Normalization
-
-The source data are scraped articles from the [Catalan wikipedia](https://ca.wikipedia.org) site.
-
-From a set of high quality, non-translation, articles in the Catalan Wikipedia, 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. (2016)](http://arxiv.org/abs/1606.05250)). In total, 15153 pairs of a question and an extracted fragment that contains the answer were created.
-
-For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.
-
-#### Who are the source language producers?
-
-Volunteers who collaborate with Catalan Wikipedia. 
-
-### 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. (2016)](http://arxiv.org/abs/1606.05250)).
-
-#### 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
-
-We hope this dataset contributes to the development of language models in Catalan, a low-resource language.
-
-### Discussion of Biases
-
-[N/A]
-
-### Other Known Limitations
-
-[N/A]
-
-## Additional Information
-
-### Dataset Curators
-
-Text Mining Unit (TeMU) at the Barcelona Supercomputing Center ([email protected])
-
-This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
-
-
-### Licensing Information
-
-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>.
-
-### 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](https://doi.org/10.5281/zenodo.4562344)
-
-
-### Contributions
-
-[N/A]

dev.json → default/viquiquad-test.parquet

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viquiquad.py

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-"""ViquiQuAD Dataset."""
-# Loading script for the ViquiQuAD dataset.
-import json
-
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = """\
-Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021). 
-ViquiQuAD: an extractive QA dataset from Catalan Wikipedia (Version ViquiQuad_v.1.0.1) 
-[Data set]. Zenodo. http://doi.org/10.5281/zenodo.4761412
-"""
-
-_DESCRIPTION = """\
-ViquiQuAD: an extractive QA dataset from Catalan Wikipedia.
-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 licence. 
-This dataset can be used to build extractive-QA and Language Models.
-Funded by the Generalitat de Catalunya, Departament de Polítiques Digitals i Administració Pública (AINA),
-MT4ALL and Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
-"""
-
-_HOMEPAGE = "https://zenodo.org/record/4562345#.YK41aqGxWUk"
-
-_URL = "https://huggingface.co/datasets/projecte-aina/viquiquad/resolve/main/"
-_TRAINING_FILE = "train.json"
-_DEV_FILE = "dev.json"
-_TEST_FILE = "test.json"
-
-
-class ViquiQuAD(datasets.GeneratorBasedBuilder):
-    """ViquiQuAD Dataset."""
-
-    VERSION = datasets.Version("1.0.1")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "context": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": [
-                        {
-                            "text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                        }
-                    ],
-                }
-            ),
-            # No default supervised_keys (as we have to pass both question
-            # and context as input).
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": f"{_URL}{_TRAINING_FILE}",
-            "dev": f"{_URL}{_DEV_FILE}",
-            "test": f"{_URL}{_TEST_FILE}",
-        }
-        downloaded_files = dl_manager.download(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            viquiquad = json.load(f)
-            for article in viquiquad["data"]:
-                title = article.get("title", "").strip()
-                for paragraph in article["paragraphs"]:
-                    context = paragraph["context"].strip()
-                    for qa in paragraph["qas"]:
-                        question = qa["question"].strip()
-                        id_ = qa["id"]
-                        # answer_starts = [answer["answer_start"] for answer in qa["answers"]]
-                        # answers = [answer["text"].strip() for answer in qa["answers"]]
-                        text = qa["answers"][0]["text"]
-                        answer_start = qa["answers"][0]["answer_start"]
-
-                        # Features currently used are "context", "question", and "answers".
-                        # Others are extracted here for the ease of future expansions.
-                        yield id_, {
-                            "title": title,
-                            "context": context,
-                            "question": question,
-                            "id": id_,
-                            "answers": [{"text": text, "answer_start": answer_start}],
-                        }