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"""args.me Dataset""" |
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import json |
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import datasets |
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_CITATION = """\ |
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@dataset{yamen_ajjour_2020_4139439, |
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author = {Yamen Ajjour and |
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Henning Wachsmuth and |
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Johannes Kiesel and |
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Martin Potthast and |
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Matthias Hagen and |
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Benno Stein}, |
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title = {args.me corpus}, |
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month = oct, |
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year = 2020, |
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publisher = {Zenodo}, |
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version = {1.0-cleaned}, |
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doi = {10.5281/zenodo.4139439}, |
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url = {https://doi.org/10.5281/zenodo.4139439} |
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} |
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""" |
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_DESCRIPTION = """\ |
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The args.me corpus (version 1.0, cleaned) comprises 382 545 arguments crawled from four debate portals in the middle of 2019. The debate portals are Debatewise, IDebate.org, Debatepedia, and Debate.org. The arguments are extracted using heuristics that are designed for each debate portal. |
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""" |
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_HOMEPAGE = "https://zenodo.org/record/4139439" |
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_LICENSE = "https://creativecommons.org/licenses/by/4.0/legalcode" |
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_REPO = "https://huggingface.co./datasets/webis/args_me/resolve/main" |
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_URLs = { |
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'corpus': f"{_REPO}/args-me.jsonl", |
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} |
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class ArgsMe(datasets.GeneratorBasedBuilder): |
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"""382,545 arguments crawled from debate portals""" |
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VERSION = datasets.Version("1.1.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="corpus", version=VERSION, description="The args.me dataset"), |
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datasets.BuilderConfig(name="topics", version=VERSION, description="The args.me dataset"), |
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datasets.BuilderConfig(name="judgments", version=VERSION, description="The args.me dataset"), |
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] |
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DEFAULT_CONFIG_NAME = "corpus" |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"argument": datasets.Value("string"), |
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"conclusion": datasets.Value("string"), |
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"stance": datasets.Value("string"), |
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"id": datasets.Value("string") |
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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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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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"""Returns SplitGenerators.""" |
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URL = _URLs[self.config.name] |
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data_file = dl_manager.download(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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"data_file": data_file, |
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}, |
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), |
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] |
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def _generate_examples(self, data_file): |
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""" Yields examples as (key, example) tuples. """ |
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with open(data_file, encoding="utf-8") as f: |
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for row in f: |
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data = json.loads(row) |
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id_ = data['id'] |
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content = data["premises"][0] |
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yield id_, { |
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"argument": content['text'], |
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"conclusion": data["conclusion"], |
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"stance": content['stance'], |
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"id": id_ |
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} |
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