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| """Catalan Textual Corpus.""" |
|
|
| import os |
|
|
| import datasets |
|
|
|
|
| _CITATION = """\ |
| @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", |
| eprint={2107.07903}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| The Catalan Textual Corpus is a 1760-million-token web corpus of Catalan built from several sources: existing corpus such as DOGC, CaWac (non-dedup version), Oscar (unshuffled version), Open Subtitles, Catalan Wikipedia; and three brand new crawlings: the Catalan General Crawling, obtained by crawling the 500 most popular .cat and .ad domains; the Catalan Government Crawling, obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government; and the ACN corpus with 220k news items from March 2015 until October 2020, crawled from the Catalan News Agency. |
| |
| It consists of 1.758.388.896 tokens, 73.172.152 sentences and 12.556.365 documents. Documents are separated by single new lines. These boundaries have been preserved as long as the license allowed it. |
| """ |
|
|
| _HOMEPAGE = "https://zenodo.org/record/4519349" |
|
|
| _LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International" |
|
|
| _URL = "https://zenodo.org/record/4519349/files/catalan_textual_corpus.zip?download=1" |
|
|
|
|
| class CatalanTextualCorpus(datasets.GeneratorBasedBuilder): |
| """Catalan Textual Corpus.""" |
|
|
| VERSION = datasets.Version("1.0.0") |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features({"text": datasets.Value("string")}), |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| data_dir = dl_manager.download_and_extract(_URL) |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "filepath": os.path.join(data_dir, "corpus", "catalan_textual_corpus.txt"), |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath): |
| with open(filepath, encoding="utf-8") as f: |
| text = "" |
| for id_, line in enumerate(f): |
| if line == "\n": |
| yield id_, {"text": text.strip()} |
| text = "" |
| else: |
| text += line |
|
|