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import json |
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from itertools import product |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """T-Rex dataset.""" |
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_NAME = "t_rex" |
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_VERSION = "0.0.7" |
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_CITATION = """ |
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@inproceedings{elsahar2018t, |
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title={T-rex: A large scale alignment of natural language with knowledge base triples}, |
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author={Elsahar, Hady and Vougiouklis, Pavlos and Remaci, Arslen and Gravier, Christophe and Hare, Jonathon and Laforest, Frederique and Simperl, Elena}, |
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booktitle={Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, |
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year={2018} |
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} |
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""" |
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_HOME_PAGE = "https://github.com/asahi417/relbert" |
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_URL = f'https://huggingface.co/datasets/relbert/{_NAME}/resolve/main/data' |
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MIN_ENTITY_FREQ = [1, 2, 3, 4] |
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MAX_PREDICATE_FREQ = [100, 50, 25, 10] |
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_TYPES = [f"filter_unified.min_entity_{a}_max_predicate_{b}" for a, b in product(MIN_ENTITY_FREQ, MAX_PREDICATE_FREQ)] |
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_NON_SPLITS = ["raw", "filter", "filter_unified"] |
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_URLS = {i: {str(datasets.Split.TRAIN): [f'{_URL}/t_rex.{i}.jsonl']} if i in _NON_SPLITS else { |
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str(datasets.Split.TRAIN): [f'{_URL}/t_rex.{i}.train.jsonl'], |
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str(datasets.Split.VALIDATION): [f'{_URL}/t_rex.{i}.validation.jsonl'], |
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str(datasets.Split.TEST): [f'{_URL}/t_rex.filter_unified.test.jsonl']} |
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for i in _TYPES} |
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class TREXConfig(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(TREXConfig, self).__init__(**kwargs) |
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class TREX(datasets.GeneratorBasedBuilder): |
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"""Dataset.""" |
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BUILDER_CONFIGS = [ |
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TREXConfig(name=i, version=datasets.Version(_VERSION), description=_DESCRIPTION) |
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for i in sorted(_TYPES) |
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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[self.config.name]) |
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if self.config.name in _NON_SPLITS: |
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return [datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepaths": downloaded_file[str(datasets.Split.TRAIN)]})] |
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else: |
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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, datasets.Split.TEST]] |
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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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"title": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"predicate": datasets.Value("string"), |
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"object": datasets.Value("string"), |
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"subject": 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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) |
