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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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ALBUQUERQUE2022,author="Albuquerque, Hidelberg O. and Costa, Rosimeire and Silvestre, Gabriel and Souza, Ellen and da Silva, N{\'a}dia F. F. and Vit{\'o}rio, Douglas and Moriyama, Gyovana and Martins, Lucas and Soezima, Luiza and Nunes, Augusto and Siqueira, Felipe and Tarrega, Jo{\~a}o P. and Beinotti, Joao V. and Dias, Marcio and Silva, Matheus and Gardini, Miguel and Silva, Vinicius and de Carvalho, Andr{\'e} C. P. L. F. and Oliveira, Adriano L. I.", title="{UlyssesNER-Br}: A Corpus of Brazilian Legislative Documents for Named Entity Recognition", booktitle="Computational Processing of the Portuguese Language", year="2022", pages="3--14",@inproceedings{inPress, PROPOR2022} |
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""" |
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_DESCRIPTION = """ |
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PL-corpus is a Portuguese language dataset for named entity recognition applied to legislative documents. Its parte of the UlyssesBR-corpus, and consists entirely of manually annotated public bills texts (projetos de leis) and contains tags for persons, locations, date entities, organizations, legal foundation and bills. |
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""" |
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_HOMEPAGE = "https://github.com/Convenio-Camara-dos-Deputados/ulyssesner-br-propor" |
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_URL = "https://raw.githubusercontent.com/bergoliveira/assessment-of-deep-learning-models-icann/main/pl-corpus/" |
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_TRAINING_FILE = "train.conll" |
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_DEV_FILE = "dev.conll" |
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_TEST_FILE = "test.conll" |
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class PlCorpus(datasets.GeneratorBasedBuilder): |
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"""pL-corpus dataset""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="pl-corpus", version=VERSION, description="PL-corpus dataset"), |
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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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"id": datasets.Value("string"), |
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"tokens": datasets.Sequence(datasets.Value("string")), |
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"ner_tags": datasets.Sequence( |
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datasets.features.ClassLabel( |
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names=[ |
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"O", |
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"B-ORGANIZACAO", |
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"I-ORGANIZACAO", |
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"B-PESSOA", |
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"I-PESSOA", |
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"B-DATA", |
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"I-DATA", |
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"B-LOCAL", |
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"I-LOCAL", |
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"B-FUNDAMENTO", |
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"I-FUNDAMENTO", |
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"B-PRODUTODELEI", |
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"I-PRODUTODELEI", |
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"B-EVENTO", |
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"I-EVENTO", |
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] |
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) |
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), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://github.com/Convenio-Camara-dos-Deputados/ulyssesner-br-propor", |
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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( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": downloaded_files["train"], "split": "train"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"filepath": downloaded_files["dev"], "split": "validation"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": downloaded_files["test"], "split": "test"}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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"""Yields examples.""" |
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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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guid = 0 |
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tokens = [] |
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ner_tags = [] |
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for line in f: |
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if line == "" or line == "\n": |
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if tokens: |
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yield guid, { |
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"id": str(guid), |
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"tokens": tokens, |
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"ner_tags": ner_tags, |
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} |
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guid += 1 |
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tokens = [] |
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ner_tags = [] |
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else: |
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splits = line.split(" ") |
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tokens.append(splits[0]) |
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ner_tags.append(splits[1].rstrip()) |
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yield guid, { |
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"id": str(guid), |
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"tokens": tokens, |
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"ner_tags": ner_tags, |
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} |
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