| import datasets | |
| import json | |
| _NAME = 'RuNNE' | |
| _CITATION = ''' | |
| @article{Artemova2022runne, | |
| title={{RuNNE-2022 Shared Task: Recognizing Nested Named Entities}}, | |
| author={Artemova, Ekaterina and Zmeev, Maksim and Loukachevitch, | |
| Natalia and Rozhkov, Igor and Batura, Tatiana and Braslavski, | |
| Pavel and Ivanov, Vladimir and Tutubalina, Elena}, | |
| journal={Computational Linguistics and Intellectual Technologies: | |
| Proceedings of the International Conference "Dialog"}, | |
| year={2022} | |
| } | |
| '''.strip() | |
| _DESCRIPTION = 'A Russian Dataset with Nested Named Entities' | |
| _HOMEPAGE = 'https://github.com/dialogue-evaluation/RuNNE' | |
| _VERSION = '1.0.0' | |
| class RuNNEBuilder(datasets.GeneratorBasedBuilder): | |
| _DATA_URLS = { | |
| 'train': 'data/train.jsonl', | |
| 'test': 'data/test.jsonl', | |
| 'dev': 'data/dev.jsonl' | |
| } | |
| _ENTITY_TYPES_URLS = { | |
| 'ent_types': 'ent_types.txt' | |
| } | |
| VERSION = datasets.Version(_VERSION) | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig('data', | |
| version=VERSION, | |
| description='Data'), | |
| datasets.BuilderConfig('ent_types', | |
| version=VERSION, | |
| description='Entity types list') | |
| ] | |
| DEFAULT_CONFIG_NAME = 'data' | |
| def _info(self) -> datasets.DatasetInfo: | |
| if self.config.name == 'data': | |
| features = datasets.Features({ | |
| 'id': datasets.Value('int32'), | |
| 'text': datasets.Value('string'), | |
| 'entities': datasets.Sequence(datasets.Value('string')) | |
| }) | |
| else: | |
| features = datasets.Features({ | |
| 'type': datasets.Value('string') | |
| }) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION | |
| ) | |
| def _split_generators(self, dl_manager: datasets.DownloadManager): | |
| if self.config.name == 'data': | |
| files = dl_manager.download(self._DATA_URLS) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={'filepath': files['train']}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={'filepath': files['test']}, | |
| ), | |
| datasets.SplitGenerator( | |
| name='dev', | |
| gen_kwargs={'filepath': files['dev']}, | |
| ), | |
| ] | |
| else: | |
| files = dl_manager.download(self._ENTITY_TYPES_URLS) | |
| return [datasets.SplitGenerator( | |
| name='ent_types', | |
| gen_kwargs={'filepath': files['ent_types']}, | |
| )] | |
| def _generate_examples(self, filepath): | |
| if self.config.name == 'data': | |
| with open(filepath, encoding='utf-8') as f: | |
| for line in f: | |
| doc = json.loads(line) | |
| yield doc['id'], doc | |
| else: | |
| with open(filepath, encoding='utf-8') as f: | |
| for i, line in enumerate(f): | |
| entity_type = line.strip() | |
| if entity_type: | |
| yield i, {'type': entity_type} | |