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"""KPWR version 1.27 dataset.""" |
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import csv |
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import datasets |
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_DESCRIPTION = "KPWR version 1.27 dataset. Prepared for Longformer." |
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_URLS = { |
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"train": "https://huggingface.co/datasets/clarin-knext/kpwr-long/resolve/main/data/train.iob", |
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"valid": "https://huggingface.co/datasets/clarin-knext/kpwr-long/resolve/main/data/valid.iob", |
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"test": "https://huggingface.co/datasets/clarin-knext/kpwr-long/resolve/main/data/test.iob", |
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} |
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_HOMEPAGE = "https://clarin-pl.eu/dspace/handle/11321/270" |
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_N82_TAGS = [ |
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'nam_adj', |
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'nam_adj_city', |
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'nam_adj_country', |
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'nam_adj_person', |
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'nam_eve', |
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'nam_eve_human', |
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'nam_eve_human_cultural', |
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'nam_eve_human_holiday', |
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'nam_eve_human_sport', |
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'nam_fac_bridge', |
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'nam_fac_goe', |
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'nam_fac_goe_stop', |
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'nam_fac_park', |
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'nam_fac_road', |
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'nam_fac_square', |
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'nam_fac_system', |
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'nam_liv_animal', |
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'nam_liv_character', |
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'nam_liv_god', |
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'nam_liv_habitant', |
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'nam_liv_person', |
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'nam_loc', |
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'nam_loc_astronomical', |
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'nam_loc_country_region', |
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'nam_loc_gpe_admin1', |
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'nam_loc_gpe_admin2', |
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'nam_loc_gpe_admin3', |
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'nam_loc_gpe_city', |
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'nam_loc_gpe_conurbation', |
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'nam_loc_gpe_country', |
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'nam_loc_gpe_district', |
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'nam_loc_gpe_subdivision', |
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'nam_loc_historical_region', |
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'nam_loc_hydronym', |
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'nam_loc_hydronym_lake', |
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'nam_loc_hydronym_ocean', |
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'nam_loc_hydronym_river', |
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'nam_loc_hydronym_sea', |
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'nam_loc_land', |
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'nam_loc_land_continent', |
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'nam_loc_land_island', |
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'nam_loc_land_mountain', |
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'nam_loc_land_peak', |
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'nam_loc_land_region', |
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'nam_num_house', |
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'nam_num_phone', |
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'nam_org_company', |
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'nam_org_group', |
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'nam_org_group_band', |
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'nam_org_group_team', |
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'nam_org_institution', |
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'nam_org_nation', |
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'nam_org_organization', |
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'nam_org_organization_sub', |
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'nam_org_political_party', |
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'nam_oth', |
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'nam_oth_currency', |
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'nam_oth_data_format', |
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'nam_oth_license', |
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'nam_oth_position', |
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'nam_oth_tech', |
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'nam_oth_www', |
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'nam_pro', |
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'nam_pro_award', |
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'nam_pro_brand', |
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'nam_pro_media', |
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'nam_pro_media_periodic', |
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'nam_pro_media_radio', |
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'nam_pro_media_tv', |
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'nam_pro_media_web', |
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'nam_pro_model_car', |
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'nam_pro_software', |
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'nam_pro_software_game', |
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'nam_pro_title', |
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'nam_pro_title_album', |
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'nam_pro_title_article', |
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'nam_pro_title_book', |
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'nam_pro_title_document', |
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'nam_pro_title_song', |
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'nam_pro_title_treaty', |
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'nam_pro_title_tv', |
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'nam_pro_vehicle' |
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] |
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_NER_IOB_TAGS = ['O'] |
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for tag in _N82_TAGS: |
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_NER_IOB_TAGS.extend([f'B-{tag}', f'I-{tag}']) |
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class KpwrDataset(datasets.GeneratorBasedBuilder): |
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def _info(self) -> datasets.DatasetInfo: |
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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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"tokens": datasets.Sequence(datasets.Value('string')), |
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"lemmas": datasets.Sequence(datasets.Value('string')), |
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"mstags": datasets.Sequence(datasets.Value('string')), |
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"ner": datasets.Sequence(datasets.features.ClassLabel(names=_NER_IOB_TAGS)) |
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} |
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), |
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homepage=_HOMEPAGE |
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) |
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def _split_generators(self, dl_manager: datasets.DownloadManager): |
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downloaded_files = dl_manager.download_and_extract(_URLS) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepath': downloaded_files['train']}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={'filepath': downloaded_files['valid']}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={'filepath': downloaded_files['test']}) |
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] |
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def _generate_examples(self, filepath: str): |
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with open(filepath, 'r', encoding='utf-8') as fin: |
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reader = csv.reader(fin, delimiter='\t', quoting=csv.QUOTE_NONE) |
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tokens = [] |
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lemmas = [] |
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mstags = [] |
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ner = [] |
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gid = 0 |
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for line in reader: |
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if not line: |
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yield gid, { |
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"tokens": tokens, |
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"lemmas": lemmas, |
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"mstags": mstags, |
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"ner": ner |
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} |
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gid += 1 |
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tokens = [] |
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lemmas = [] |
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mstags = [] |
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ner = [] |
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elif len(line) == 1: |
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continue |
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else: |
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tokens.append(line[0]) |
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lemmas.append(line[1]) |
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mstags.append(line[2]) |
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ner.append(line[3]) |
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