# coding=utf-8 # Copyright 2020 HuggingFace Datasets Authors. # Modified by Vésteinn Snæbjarnarson 2021 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Lint as: python3 LABELS = [ "ACSFPA", "ACSFPD", "ACSFPN", "ACSFSA", "ACSFSD", "ACSFSN", "ACSMPA", "ACSMPD", "ACSMPN", "ACSMSA", "ACSMSD", "ACSMSN", "ACSNPA", "ACSNPD", "ACSNPN", "ACSNSA", "ACSNSD", "ACSNSN", "ACWFPA", "ACWFPD", "ACWFPN", "ACWFSA", "ACWFSD", "ACWFSN", "ACWMPD", "ACWMPN", "ACWMSA", "ACWMSN", "ACWNPA", "ACWNPD", "ACWNPN", "ACWNSA", "ACWNSN", "AI", "APSFPA", "APSFPD", "APSFPN", "APSFSA", "APSFSD", "APSFSN", "APSMPA", "APSMPD", "APSMPN", "APSMSA", "APSMSD", "APSMSN", "APSNPA", "APSNPD", "APSNPN", "APSNSA", "APSNSD", "APSNSN", "APWFPA", "APWFPD", "APWFPG", "APWFPN", "APWFSA", "APWFSD", "APWFSG", "APWFSN", "APWMPA", "APWMPD", "APWMPN", "APWMSA", "APWMSD", "APWMSN", "APWNPA", "APWNPD", "APWNPN", "APWNSA", "APWNSD", "APWNSN", "ASSFPD", "ASSFPN", "ASSFSA", "ASSFSD", "ASSFSN", "ASSMPA", "ASSMPN", "ASSMSA", "ASSMSD", "ASSMSN", "ASSNPA", "ASSNPD", "ASSNPN", "ASSNSA", "ASSNSD", "ASSNSN", "ASWFPA", "ASWFPD", "ASWFPN", "ASWFSA", "ASWFSD", "ASWFSN", "ASWMPA", "ASWMPD", "ASWMPN", "ASWMSA", "ASWMSD", "ASWMSN", "ASWNPA", "ASWNPD", "ASWNPN", "ASWNSA", "ASWNSD", "ASWNSN", "C", "CI", "CR", "DCG", "DCN", "DG", "DI", "DN", "DSG", "DSN", "F", "KC", "KE", "KO", "KQ", "M", "NC", "NCFPA", "NCFPD", "NCFPN", "NCFSA", "NCFSN", "NCMPA", "NCMPD", "NCMPG", "NCMPN", "NCMSA", "NCMSN", "NCNPA", "NCNPD", "NCNPN", "NCNSA", "NCNSD", "NCNSN", "NO", "NP", "NR", "PBFPA", "PBFPD", "PBFPN", "PBFSA", "PBFSD", "PBFSN", "PBMPA", "PBMPD", "PBMPN", "PBMSA", "PBMSD", "PBMSN", "PBNPA", "PBNPD", "PBNPN", "PBNSA", "PBNSD", "PBNSN", "PDFPA", "PDFPD", "PDFPN", "PDFSA", "PDFSD", "PDFSN", "PDMPA", "PDMPD", "PDMPN", "PDMSA", "PDMSD", "PDMSN", "PDNPA", "PDNPD", "PDNPN", "PDNSA", "PDNSD", "PDNSN", "PEMPA", "PEMSA", "PENSA", "PENSG", "PIFPA", "PIFPD", "PIFPN", "PIFSA", "PIFSD", "PIFSN", "PIMPA", "PIMPD", "PIMPN", "PIMSA", "PIMSD", "PIMSN", "PINPA", "PINPD", "PINPN", "PINSA", "PINSD", "PINSN", "PP1PA", "PP1PD", "PP1PG", "PP1PN", "PP1SA", "PP1SD", "PP1SG", "PP1SN", "PP2PG", "PP2PN", "PP2SA", "PP2SD", "PP2SG", "PP2SN", "PPFPA", "PPFPD", "PPFPG", "PPFPN", "PPFSA", "PPFSD", "PPFSG", "PPFSN", "PPMPA", "PPMPD", "PPMPG", "PPMPN", "PPMSA", "PPMSD", "PPMSG", "PPMSN", "PPNPA", "PPNPD", "PPNPG", "PPNPN", "PPNSA", "PPNSD", "PPNSG", "PPNSN", "PQFPA", "PQFPN", "PQFSA", "PQFSD", "PQFSN", "PQMPN", "PQMSA", "PQMSD", "PQMSN", "PQNSA", "PQNSD", "PQNSN", "SFPA", "SFPAA", "SFPAP", "SFPD", "SFPDA", "SFPDAP", "SFPDP", "SFPG", "SFPGP", "SFPN", "SFPNA", "SFPNP", "SFSA", "SFSAA", "SFSAAP", "SFSAP", "SFSD", "SFSDA", "SFSDAP", "SFSDP", "SFSG", "SFSGA", "SFSGP", "SFSN", "SFSNA", "SFSNAP", "SFSNP", "SMPA", "SMPAA", "SMPD", "SMPDA", "SMPDP", "SMPG", "SMPGA", "SMPN", "SMPNA", "SMSA", "SMSAA", "SMSAP", "SMSD", "SMSDA", "SMSDAP", "SMSDP", "SMSG", "SMSGA", "SMSGP", "SMSN", "SMSNA", "SMSNAP", "SMSNP", "SNPA", "SNPAA", "SNPD", "SNPDA", "SNPDP", "SNPG", "SNPGA", "SNPN", "SNPNA", "SNPNP", "SNSA", "SNSAA", "SNSAAP", "SNSAP", "SNSD", "SNSDA", "SNSDAP", "SNSDP", "SNSG", "SNSGA", "SNSGP", "SNSN", "SNSNA", "SNSNAP", "SNSNP", "SX", "SXP", "SXSD", "SXSG", "TS", "TT", "VAFPA", "VAFPD", "VAFPN", "VAFSA", "VAFSD", "VAFSN", "VAMPA", "VAMPD", "VAMPN", "VAMSA", "VAMSD", "VAMSN", "VANPA", "VANPD", "VANPN", "VANSA", "VANSD", "VANSN", "VE", "VEAP", "VEAS2", "VEAS3", "VEPP", "VEPS1", "VEPS2", "VEPS3", "VI", "VMP", "VMS", "VNAP", "VNAS1", "VNAS2", "VNAS3", "VNPP", "VNPS1", "VNPS2", "VNPS3", "VP", "W", "X" ] import datasets logger = datasets.logging.get_logger(__name__) _CITATION = """\ @misc{sosialurin-pos, title = {Marking av teldutøkum tekstsavn}, author = {Zakaris Svabo Hansen, Heini Justinussen, and Mortan Ólason}, url = {http://ark.axeltra.com/index.php?type=person&lng=en&id=18}, year = {2004} } """ _DESCRIPTION = """\ The corpus that has been created consists of ca. 100.000 words of text from the [Faroese] newspaper Sosialurin. Each word is tagged with grammatical information (word class, gender, number etc.) """ _URL = "https://huggingface.co/datasets/vesteinn/sosialurin-faroese-pos/raw/main/" _TRAINING_FILE = "fo.revised.txt" class SosialurinPOSConfig(datasets.BuilderConfig): """BuilderConfig for sosialurin-faroese-pos""" def __init__(self, **kwargs): """BuilderConfig for sosialurin-faroese-pos. Args: **kwargs: keyword arguments forwarded to super. """ super(SosialurinPOSConfig, self).__init__(**kwargs) class SosialurinPOS(datasets.GeneratorBasedBuilder): """sosialurin-faroese-pos dataset.""" BUILDER_CONFIGS = [ SosialurinPOSConfig(name="sosialurin-faroese-pos", version=datasets.Version("0.1.0"), description="sosialurin-faroese-pos dataset"), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("string"), "tokens": datasets.Sequence(datasets.Value("string")), "pos_tags": datasets.Sequence( datasets.features.ClassLabel( names=LABELS ) ), } ), supervised_keys=None, homepage="http://ark.axeltra.com/index.php?type=person&lng=en&id=18", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" urls_to_download = { "train": f"{_URL}{_TRAINING_FILE}", } downloaded_files = dl_manager.download_and_extract(urls_to_download) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), ] def _generate_examples(self, filepath): logger.info("⏳ Generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as f: guid = 0 tokens = [] pos_tags = [] for line in f: if line.startswith("-DOCSTART-") or line == "" or line == "\n": if tokens: yield guid, { "id": str(guid), "tokens": tokens, "pos_tags": pos_tags, } guid += 1 tokens = [] pos_tags = [] else: # tokens are tab separated splits = line.split("\t") tokens.append(splits[0]) try: pos_tags.append(splits[1].rstrip()) except: print(splits) raise # last example yield guid, { "id": str(guid), "tokens": tokens, "pos_tags": pos_tags, }