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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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_DESCRIPTION = """[Relation Mapping](https://www.jair.org/index.php/jair/article/view/10583)""" |
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_NAME = "Relation Mapping" |
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_VERSION = "1.0.0" |
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_CITATION = """ |
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@article{turney2008latent, |
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title={The latent relation mapping engine: Algorithm and experiments}, |
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author={Turney, Peter D}, |
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journal={Journal of Artificial Intelligence Research}, |
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volume={33}, |
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pages={615--655}, |
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year={2008} |
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} |
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""" |
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_HOME_PAGE = "https://github.com/asahi417/relbert" |
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_URLS = { |
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str(datasets.Split.TEST): [f'https://huggingface.co/datasets/relbert/{_NAME}/raw/main/data.jsonl'] |
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} |
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class RelationMappingConfig(datasets.BuilderConfig): |
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"""BuilderConfig""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(RelationMappingConfig, self).__init__(**kwargs) |
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class RelationMapping(datasets.GeneratorBasedBuilder): |
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"""Dataset.""" |
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BUILDER_CONFIGS = [ |
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RelationMappingConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION), |
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] |
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def _split_generators(self, dl_manager): |
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downloaded_file = dl_manager.download_and_extract(_URLS) |
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return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]}) |
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for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION]] |
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def _generate_examples(self, filepaths): |
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_key = 0 |
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for filepath in filepaths: |
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logger.info(f"generating examples from = {filepath}") |
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with open(filepath, encoding="utf-8") as f: |
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_list = [i for i in f.read().split('\n') if len(i) > 0] |
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for i in _list: |
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data = json.loads(i) |
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yield _key, data |
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_key += 1 |
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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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"reference": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), |
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"source": datasets.Sequence(datasets.Value("string")), |
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"target": datasets.Sequence(datasets.Value("string")), |
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"agreement": datasets.Sequence(datasets.Value("float32")), |
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"pos": datasets.Sequence(datasets.Value("string")), |
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"target_random": datasets.Sequence(datasets.Value("string")), |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOME_PAGE, |
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citation=_CITATION, |
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) |
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