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"""DanFEVER: A FEVER dataset for Danish""" |
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import csv |
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import os |
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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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@inproceedings{norregaard-derczynski-2021-danfever, |
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title = "{D}an{FEVER}: claim verification dataset for {D}anish", |
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author = "N{\o}rregaard, Jeppe and |
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Derczynski, Leon", |
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booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)", |
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month = may # " 31--2 " # jun, |
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year = "2021", |
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address = "Reykjavik, Iceland (Online)", |
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publisher = {Link{\"o}ping University Electronic Press, Sweden}, |
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url = "https://aclanthology.org/2021.nodalida-main.47", |
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pages = "422--428", |
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abstract = "We present a dataset, DanFEVER, intended for multilingual misinformation research. The dataset is in Danish and has the same format as the well-known English FEVER dataset. It can be used for testing methods in multilingual settings, as well as for creating models in production for the Danish language.", |
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} |
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""" |
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_DESCRIPTION = """\ |
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""" |
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_URL = "https://media.githubusercontent.com/media/StrombergNLP/danfever/main/tsv/da_fever.tsv" |
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class DanFeverConfig(datasets.BuilderConfig): |
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"""BuilderConfig for DanFever""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig DanFever. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(DanFeverConfig, self).__init__(**kwargs) |
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class DanFever(datasets.GeneratorBasedBuilder): |
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"""DanFever dataset.""" |
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BUILDER_CONFIGS = [ |
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DanFeverConfig(name="DanFever", version=datasets.Version("1.0.0"), description="FEVER dataset for Danish"), |
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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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"claim": datasets.Value("string"), |
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"label": datasets.features.ClassLabel( |
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names=[ |
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"Refuted", |
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"Supported", |
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"NotEnoughInfo", |
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] |
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), |
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"evidence_extract": datasets.Value("string"), |
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"verifiable": datasets.features.ClassLabel( |
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names=[ |
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"NotVerifiable", |
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"Verifiable", |
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] |
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), |
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"evidence": datasets.Value("string"), |
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"original_id": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://stromberg.ai/publication/danfever/", |
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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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downloaded_file = dl_manager.download_and_extract(_URL) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}), |
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] |
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def _generate_examples(self, filepath): |
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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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data_reader = csv.DictReader(f, delimiter="\t", quotechar='"') |
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guid = 0 |
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for instance in data_reader: |
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instance.pop('nr.') |
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instance["original_id"] = instance.pop('id') |
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instance["id"] = str(guid) |
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yield guid, instance |
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guid += 1 |
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