# coding=utf-8 """CEN dataset.""" import csv import datasets _DESCRIPTION = "CEN dataset." _URLS = { "train": "https://huggingface.co/datasets/clarin-knext/cen/resolve/main/data/train.iob", "valid": "https://huggingface.co/datasets/clarin-knext/cen/resolve/main/data/valid.iob", "test": "https://huggingface.co/datasets/clarin-knext/cen/resolve/main/data/test.iob", } _HOMEPAGE = "https://clarin-pl.eu/dspace/handle/11321/6" with open('data/n82_tagset.txt', 'r') as fin: _N82_TAGS = fin.read().split('\n') _NER_IOB_TAGS = ['O'] for tag in _N82_TAGS: _NER_IOB_TAGS.extend([f'B-{tag}', f'I-{tag}']) class CenDataset(datasets.GeneratorBasedBuilder): def _info(self) -> datasets.DatasetInfo: return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "tokens": datasets.Sequence(datasets.Value('string')), "lemmas": datasets.Sequence(datasets.Value('string')), "mstags": datasets.Sequence(datasets.Value('string')), "ner": datasets.Sequence(datasets.features.ClassLabel(names=_NER_IOB_TAGS)) } ), homepage=_HOMEPAGE ) def _split_generators(self, dl_manager: datasets.DownloadManager): downloaded_files = dl_manager.download_and_extract(_URLS) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepath': downloaded_files['train']}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={'filepath': downloaded_files['valid']}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={'filepath': downloaded_files['test']}) ] def _generate_examples(self, filepath: str): with open(filepath, 'r', encoding='utf-8') as fin: reader = csv.reader(fin, delimiter='\t', quoting=csv.QUOTE_NONE) tokens = [] lemmas = [] mstags = [] ner = [] gid = 0 for line in reader: if not line: yield gid, { "tokens": tokens, "lemmas": lemmas, "mstags": mstags, "ner": ner } gid += 1 tokens = [] lemmas = [] mstags = [] ner = [] elif len(line) == 1: # ignore --DOCSTART lines continue else: tokens.append(line[0]) lemmas.append(line[1]) mstags.append(line[2]) ner.append(line[3])