""" NER dataset compiled by T-NER library https://github.com/asahi417/tner/tree/master/tner """ import json from itertools import chain import datasets logger = datasets.logging.get_logger(__name__) _DESCRIPTION = """[ontonotes5 NER dataset](https://aclanthology.org/N06-2015/)""" _NAME = "ontonotes5" _VERSION = "1.0.0" _CITATION = """ @inproceedings{hovy-etal-2006-ontonotes, title = "{O}nto{N}otes: The 90{\%} Solution", author = "Hovy, Eduard and Marcus, Mitchell and Palmer, Martha and Ramshaw, Lance and Weischedel, Ralph", booktitle = "Proceedings of the Human Language Technology Conference of the {NAACL}, Companion Volume: Short Papers", month = jun, year = "2006", address = "New York City, USA", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/N06-2015", pages = "57--60", } """ _HOME_PAGE = "https://github.com/asahi417/tner" _URL = f'https://huggingface.co/datasets/tner/{_NAME}/raw/main/dataset' _URLS = { str(datasets.Split.TEST): [f'{_URL}/test.json'], str(datasets.Split.TRAIN): [f'{_URL}/train{i:02d}.json' for i in range(4)], str(datasets.Split.VALIDATION): [f'{_URL}/valid.json'], } class Ontonotes5Config(datasets.BuilderConfig): """BuilderConfig""" def __init__(self, **kwargs): """BuilderConfig. Args: **kwargs: keyword arguments forwarded to super. """ super(Ontonotes5Config, self).__init__(**kwargs) class Ontonotes5(datasets.GeneratorBasedBuilder): """Dataset.""" BUILDER_CONFIGS = [ Ontonotes5Config(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, datasets.Split.TEST]] 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( { "tokens": datasets.Sequence(datasets.Value("string")), "tags": datasets.Sequence(datasets.Value("int32")), } ), supervised_keys=None, homepage=_HOME_PAGE, citation=_CITATION, )