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from pathlib import Path |
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import datasets |
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import pandas as pd |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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@inproceedings{augustyniak-etal-2020-political, |
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title = "Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections", |
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author = "Augustyniak, Lukasz and |
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Rajda, Krzysztof and |
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Kajdanowicz, Tomasz and |
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Bernaczyk, Micha{\l}", |
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booktitle = "Proceedings of the The Fourth Widening Natural Language Processing Workshop", |
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month = jul, |
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year = "2020", |
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address = "Seattle, USA", |
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publisher = "Association for Computational Linguistics", |
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url = "https://www.aclweb.org/anthology/2020.winlp-1.28", |
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pages = "110--114" |
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} |
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""" |
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_DESCRIPTION = "Polish Political Advertising Dataset" |
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_HOMEPAGE = "https://github.com/laugustyniak/misinformation" |
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DATA_PATH = Path(".") |
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class PoliticalAdvertisingConfig(datasets.BuilderConfig): |
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def __init__(self, **kwargs): |
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super(PoliticalAdvertisingConfig, self).__init__(**kwargs) |
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class PoliticalAdvertisingDataset(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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TRAIN_FILE = DATA_PATH / "train.json" |
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VAL_FILE = DATA_PATH / "dev.json" |
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TEST_FILE = DATA_PATH / "test.json" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="political-advertising-pl", version=VERSION) |
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] |
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def _info(self): |
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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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"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-DEFENSE_AND_SECURITY", |
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"I-DEFENSE_AND_SECURITY", |
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"B-EDUCATION", |
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"I-EDUCATION", |
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"B-FOREIGN_POLICY", |
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"I-FOREIGN_POLICY", |
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"B-HEALHCARE", |
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"I-HEALHCARE", |
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"B-IMMIGRATION", |
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"I-IMMIGRATION", |
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"B-INFRASTRUCTURE_AND_ENVIROMENT", |
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"I-INFRASTRUCTURE_AND_ENVIROMENT", |
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"B-POLITICAL_AND_LEGAL_SYSTEM", |
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"I-POLITICAL_AND_LEGAL_SYSTEM", |
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"B-SOCIETY", |
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"I-SOCIETY", |
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"B-WELFARE", |
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"I-WELFARE", |
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] |
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) |
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), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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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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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, gen_kwargs={"filepath": str(self.TRAIN_FILE)} |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, gen_kwargs={"filepath": str(self.TEST_FILE)} |
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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": str(self.VAL_FILE)}, |
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), |
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] |
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def _generate_examples(self, filepath: str): |
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logger.info("⏳ Generating examples from = %s", filepath) |
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df = pd.read_json(filepath) |
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for row_id, row in df.iterrows(): |
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yield row_id, { |
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"id": row.id, |
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"text": row.text, |
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"tags": row.tags, |
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"url": row.url, |
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"tweet_id": row.tweet_id, |
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} |
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