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"""KPWR-NER tagging dataset.""" |
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import csv |
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from typing import List, Tuple, Dict, Generator |
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import datasets |
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_DESCRIPTION = """KPWR-NER tagging dataset.""" |
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_URLS = { |
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"train": "https://huggingface.co/datasets/clarin-pl/kpwr-ner/resolve/main/data/kpwr-ner-n82-train-tune.iob", |
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"test": "https://huggingface.co/datasets/clarin-pl/kpwr-ner/resolve/main/data/kpwr-ner-n82-test.iob", |
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} |
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_HOMEPAGE = "https://clarin-pl.eu/dspace/handle/11321/294" |
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_NER_TAGS = [ |
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"B-nam_adj", |
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"B-nam_adj_city", |
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"B-nam_adj_country", |
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"B-nam_adj_person", |
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"B-nam_eve", |
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"B-nam_eve_human", |
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"B-nam_eve_human_cultural", |
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"B-nam_eve_human_holiday", |
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"B-nam_eve_human_sport", |
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"B-nam_fac_bridge", |
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"B-nam_fac_goe", |
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"B-nam_fac_goe_stop", |
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"B-nam_fac_park", |
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"B-nam_fac_road", |
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"B-nam_fac_square", |
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"B-nam_fac_system", |
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"B-nam_liv_animal", |
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"B-nam_liv_character", |
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"B-nam_liv_god", |
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"B-nam_liv_habitant", |
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"B-nam_liv_person", |
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"B-nam_loc", |
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"B-nam_loc_astronomical", |
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"B-nam_loc_country_region", |
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"B-nam_loc_gpe_admin1", |
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"B-nam_loc_gpe_admin2", |
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"B-nam_loc_gpe_admin3", |
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"B-nam_loc_gpe_city", |
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"B-nam_loc_gpe_conurbation", |
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"B-nam_loc_gpe_country", |
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"B-nam_loc_gpe_district", |
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"B-nam_loc_gpe_subdivision", |
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"B-nam_loc_historical_region", |
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"B-nam_loc_hydronym", |
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"B-nam_loc_hydronym_lake", |
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"B-nam_loc_hydronym_ocean", |
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"B-nam_loc_hydronym_river", |
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"B-nam_loc_hydronym_sea", |
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"B-nam_loc_land", |
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"B-nam_loc_land_continent", |
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"B-nam_loc_land_island", |
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"B-nam_loc_land_mountain", |
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"B-nam_loc_land_peak", |
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"B-nam_loc_land_region", |
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"B-nam_num_house", |
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"B-nam_num_phone", |
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"B-nam_org_company", |
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"B-nam_org_group", |
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"B-nam_org_group_band", |
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"B-nam_org_group_team", |
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"B-nam_org_institution", |
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"B-nam_org_nation", |
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"B-nam_org_organization", |
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"B-nam_org_organization_sub", |
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"B-nam_org_political_party", |
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"B-nam_oth", |
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"B-nam_oth_currency", |
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"B-nam_oth_data_format", |
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"B-nam_oth_license", |
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"B-nam_oth_position", |
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"B-nam_oth_tech", |
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"B-nam_oth_www", |
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"B-nam_pro", |
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"B-nam_pro_award", |
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"B-nam_pro_brand", |
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"B-nam_pro_media", |
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"B-nam_pro_media_periodic", |
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"B-nam_pro_media_radio", |
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"B-nam_pro_media_tv", |
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"B-nam_pro_media_web", |
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"B-nam_pro_model_car", |
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"B-nam_pro_software", |
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"B-nam_pro_software_game", |
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"B-nam_pro_title", |
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"B-nam_pro_title_album", |
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"B-nam_pro_title_article", |
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"B-nam_pro_title_book", |
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"B-nam_pro_title_document", |
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"B-nam_pro_title_song", |
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"B-nam_pro_title_treaty", |
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"B-nam_pro_title_tv", |
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"B-nam_pro_vehicle", |
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"I-nam_adj_country", |
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"I-nam_eve", |
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"I-nam_eve_human", |
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"I-nam_eve_human_cultural", |
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"I-nam_eve_human_holiday", |
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"I-nam_eve_human_sport", |
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"I-nam_fac_bridge", |
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"I-nam_fac_goe", |
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"I-nam_fac_goe_stop", |
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"I-nam_fac_park", |
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"I-nam_fac_road", |
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"I-nam_fac_square", |
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"I-nam_fac_system", |
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"I-nam_liv_animal", |
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"I-nam_liv_character", |
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"I-nam_liv_god", |
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"I-nam_liv_person", |
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"I-nam_loc", |
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"I-nam_loc_astronomical", |
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"I-nam_loc_country_region", |
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"I-nam_loc_gpe_admin1", |
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"I-nam_loc_gpe_admin2", |
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"I-nam_loc_gpe_admin3", |
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"I-nam_loc_gpe_city", |
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"I-nam_loc_gpe_conurbation", |
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"I-nam_loc_gpe_country", |
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"I-nam_loc_gpe_district", |
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"I-nam_loc_gpe_subdivision", |
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"I-nam_loc_historical_region", |
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"I-nam_loc_hydronym", |
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"I-nam_loc_hydronym_lake", |
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"I-nam_loc_hydronym_ocean", |
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"I-nam_loc_hydronym_river", |
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"I-nam_loc_hydronym_sea", |
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"I-nam_loc_land", |
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"I-nam_loc_land_continent", |
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"I-nam_loc_land_island", |
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"I-nam_loc_land_mountain", |
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"I-nam_loc_land_peak", |
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"I-nam_loc_land_region", |
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"I-nam_num_house", |
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"I-nam_num_phone", |
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"I-nam_org_company", |
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"I-nam_org_group", |
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"I-nam_org_group_band", |
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"I-nam_org_group_team", |
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"I-nam_org_institution", |
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"I-nam_org_nation", |
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"I-nam_org_organization", |
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"I-nam_org_organization_sub", |
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"I-nam_org_political_party", |
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"I-nam_oth", |
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"I-nam_oth_currency", |
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"I-nam_oth_data_format", |
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"I-nam_oth_license", |
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"I-nam_oth_position", |
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"I-nam_oth_tech", |
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"I-nam_oth_www", |
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"I-nam_pro", |
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"I-nam_pro_award", |
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"I-nam_pro_brand", |
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"I-nam_pro_media", |
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"I-nam_pro_media_periodic", |
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"I-nam_pro_media_radio", |
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"I-nam_pro_media_tv", |
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"I-nam_pro_media_web", |
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"I-nam_pro_model_car", |
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"I-nam_pro_software", |
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"I-nam_pro_software_game", |
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"I-nam_pro_title", |
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"I-nam_pro_title_album", |
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"I-nam_pro_title_article", |
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"I-nam_pro_title_book", |
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"I-nam_pro_title_document", |
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"I-nam_pro_title_song", |
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"I-nam_pro_title_treaty", |
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"I-nam_pro_title_tv", |
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"I-nam_pro_vehicle", |
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"O", |
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] |
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class KPWRNER(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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"orth": datasets.Sequence(datasets.Value("string")), |
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"ner": datasets.Sequence( |
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datasets.features.ClassLabel( |
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names=_NER_TAGS, num_classes=len(_NER_TAGS) |
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) |
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), |
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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( |
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self, dl_manager: datasets.DownloadManager |
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) -> List[datasets.SplitGenerator]: |
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urls_to_download = _URLS |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": downloaded_files["train"]}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": downloaded_files["test"]}, |
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), |
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] |
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def _generate_examples( |
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self, filepath: str |
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) -> Generator[Tuple[int, Dict[str, str]], None, None]: |
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with open(filepath, "r", encoding="utf-8") as f: |
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reader = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE) |
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tokens = [] |
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lemma = [] |
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orth = [] |
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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": lemma, |
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"orth": orth, |
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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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lemma = [] |
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orth = [] |
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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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lemma.append(line[1]) |
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orth.append(line[2]) |
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ner.append(line[3]) |
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