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"""Catalan General Crawling.""" |
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import os |
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import datasets |
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_CITATION = """\ |
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@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 |
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Gonzalez-Agirre, Aitor and |
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Melero, Maite and |
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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", |
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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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eprint={2107.07903}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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""" |
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_DESCRIPTION = """\ |
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The Catalan General Crawling Corpus is a 435-million-token web corpus of Catalan built from the web. It has been obtained by crawling the 500 most popular .cat and .ad domains during July 2020. It consists of 434.817.705 tokens, 19.451.691 sentences and 1.016.114 documents. Documents are separated by single new lines. It is a subcorpus of the Catalan Textual Corpus. |
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""" |
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_HOMEPAGE = "https://zenodo.org/record/5483031#.YapO3boo9PY" |
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_LICENSE = "Creative Commons Attribution 4.0 International" |
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_URL = "https://zenodo.org/record/5483031/files/catalan_general_crawling.zip?download=1" |
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class CatalanGeneralCrawling(datasets.GeneratorBasedBuilder): |
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"""Catalan General Crawling.""" |
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VERSION = datasets.Version("1.0.0") |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features({"text": datasets.Value("string")}), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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data_dir = dl_manager.download_and_extract(_URL) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": os.path.join( |
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data_dir, "catalan_general_crawling", "corpus", "catalan_general_crawling.txt" |
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), |
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}, |
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), |
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] |
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def _generate_examples(self, filepath): |
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with open(filepath, encoding="utf-8") as f: |
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text = "" |
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for id_, line in enumerate(f): |
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if line == "\n": |
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yield id_, {"text": text.strip()} |
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text = "" |
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else: |
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text += line |
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