import json import datasets logger = datasets.logging.get_logger(__name__) _DESCRIPTION = """[SemEVAL 2012 task 2: Relational Similarity](https://aclanthology.org/S12-1047/)""" _NAME = "semeval2012_relational_similarity_v2" _VERSION = "1.0.1" _CITATION = """ @inproceedings{jurgens-etal-2012-semeval, title = "{S}em{E}val-2012 Task 2: Measuring Degrees of Relational Similarity", author = "Jurgens, David and Mohammad, Saif and Turney, Peter and Holyoak, Keith", booktitle = "*{SEM} 2012: The First Joint Conference on Lexical and Computational Semantics {--} Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation ({S}em{E}val 2012)", month = "7-8 " # jun, year = "2012", address = "Montr{\'e}al, Canada", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/S12-1047", pages = "356--364", } """ _HOME_PAGE = "https://github.com/asahi417/relbert" _URL = f'https://huggingface.co/datasets/relbert/{_NAME}/raw/main/dataset' _URLS = { str(datasets.Split.TRAIN): [f'{_URL}/train.jsonl'], str(datasets.Split.VALIDATION): [f'{_URL}/valid.jsonl'], } class SemEVAL2012RelationalSimilarityV2Config(datasets.BuilderConfig): """BuilderConfig""" def __init__(self, **kwargs): """BuilderConfig. Args: **kwargs: keyword arguments forwarded to super. """ super(SemEVAL2012RelationalSimilarityV2Config, self).__init__(**kwargs) class SemEVAL2012RelationalSimilarityV2(datasets.GeneratorBasedBuilder): """Dataset.""" BUILDER_CONFIGS = [ SemEVAL2012RelationalSimilarityV2Config(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION), ] def _split_generators(self, dl_manager): downloaded_file = dl_manager.download_and_extract(_URLS) return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]}) for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION]] def _generate_examples(self, filepaths): _key = 0 for filepath in filepaths: logger.info(f"generating examples from = {filepath}") with open(filepath, encoding="utf-8") as f: _list = [i for i in f.read().split('\n') if len(i) > 0] for i in _list: data = json.loads(i) yield _key, data _key += 1 def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "relation_type": datasets.Value("string"), "positives": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), "negatives": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), } ), supervised_keys=None, homepage=_HOME_PAGE, citation=_CITATION, )