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import json |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """ |
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Baucells, Irene, Carrino, Casimiro Pio, Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021). |
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TeCla: Text Classification Catalan dataset (Version 2.0) [Data set]. |
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Zenodo. http://doi.org/10.5281/zenodo.7334110 |
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""" |
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_DESCRIPTION = """ |
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TeCla: Text Classification Catalan dataset |
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Catalan News corpus for Text classification, crawled from ACN (Catalan News Agency) site: www.acn.cat |
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Corpus de notícies en català per a classificació textual, extret del web de l'Agència Catalana de Notícies - www.acn.cat |
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""" |
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_HOMEPAGE = """https://zenodo.org/record/4761505""" |
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_URL = "./" |
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_TRAINING_FILE = "train.json" |
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_DEV_FILE = "dev.json" |
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_TEST_FILE = "test.json" |
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class teclaConfig(datasets.BuilderConfig): |
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""" Builder config for the TeCla dataset """ |
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def __init__(self, **kwargs): |
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"""BuilderConfig for TeCla. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(teclaConfig, self).__init__(**kwargs) |
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class tecla(datasets.GeneratorBasedBuilder): |
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""" TeCla Dataset """ |
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BUILDER_CONFIGS = [ |
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teclaConfig( |
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name="tecla", |
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version=datasets.Version("1.0.1"), |
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description="tecla 2.0 dataset", |
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), |
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] |
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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( |
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{ |
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"text": datasets.Value("string"), |
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"label1": datasets.features.ClassLabel |
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(names= |
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[ |
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"Societat", |
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"Pol\u00edtica", |
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"Economia", |
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"Cultura", |
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] |
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), |
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"label2": datasets.features.ClassLabel |
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(names= |
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[ |
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"Llengua", |
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"Infraestructures", |
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"Arts", |
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"Parlament", |
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"Noves tecnologies", |
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"Castells", |
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"Successos", |
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"Empresa", |
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"Mobilitat", |
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"Teatre", |
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"Treball", |
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"Log\u00edstica", |
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"Urbanisme", |
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"Govern", |
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"Entitats", |
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"Finances", |
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"Govern espanyol", |
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"Tr\u00e0nsit", |
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"Ind\u00fastria", |
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"Esports", |
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"Exteriors", |
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"Medi ambient", |
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"Habitatge", |
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"Salut", |
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"Equipaments i patrimoni", |
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"Recerca", |
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"Cooperaci\u00f3", |
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"Innovaci\u00f3", |
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"Agroalimentaci\u00f3", |
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"Policial", |
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"Serveis Socials", |
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"Cinema", |
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"Mem\u00f2ria hist\u00f2rica", |
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"Turisme", |
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"Pol\u00edtica municipal", |
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"Comer\u00e7", |
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"Universitats", |
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"Hisenda", |
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"Judicial", |
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"Partits", |
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"M\u00fasica", |
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"Lletres", |
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"Religi\u00f3", |
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"Festa i cultura popular", |
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"Uni\u00f3 Europea", |
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"Moda", |
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"Moviments socials", |
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"Comptes p\u00fablics", |
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"Immigraci\u00f3", |
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"Educaci\u00f3", |
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"Gastronomia", |
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"Meteorologia", |
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"Energia" |
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] |
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), |
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} |
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), |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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urls_to_download = { |
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"train": f"{_URL}{_TRAINING_FILE}", |
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"dev": f"{_URL}{_DEV_FILE}", |
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"test": f"{_URL}{_TEST_FILE}", |
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} |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), |
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] |
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def _generate_examples(self, filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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logger.info("generating examples from = %s", filepath) |
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with open(filepath, encoding="utf-8") as f: |
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acn_ca = json.load(f) |
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for id_, article in enumerate(acn_ca["data"]): |
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text = article["sentence"] |
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label1 = article["label1"] |
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label2 = article["label2"] |
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yield id_, { |
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"text": text, |
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"label1": label1, |
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"label2": label2, |
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} |
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