# coding=utf-8 # Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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. import re from pathlib import Path from typing import Dict, List, Tuple import datasets from nusacrowd.utils import schemas from nusacrowd.utils.configs import NusantaraConfig from nusacrowd.utils.constants import Tasks _CITATION = """\ @data{FK2/VTAHRH_2022, author = {ARDIYANTI SURYANI, ARIE and Widyantoro, Dwi Hendratmo and Purwarianti, Ayu and Sudaryat, Yayat}, publisher = {Telkom University Dataverse}, title = {{PoSTagged Sundanese Monolingual Corpus}}, year = {2022}, version = {DRAFT VERSION}, doi = {10.34820/FK2/VTAHRH}, url = {https://doi.org/10.34820/FK2/VTAHRH} } @INPROCEEDINGS{7437678, author={Suryani, Arie Ardiyanti and Widyantoro, Dwi Hendratmo and Purwarianti, Ayu and Sudaryat, Yayat}, booktitle={2015 International Conference on Information Technology Systems and Innovation (ICITSI)}, title={Experiment on a phrase-based statistical machine translation using PoS Tag information for Sundanese into Indonesian}, year={2015}, volume={}, number={}, pages={1-6}, doi={10.1109/ICITSI.2015.7437678} } """ _LANGUAGES = ["sun"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data) _LOCAL = False _DATASETNAME = "postag_su" _DESCRIPTION = """\ This dataset contains 3616 lines of Sundanese sentences taken from several online magazines (Mangle, Dewan Dakwah Jabar, and Balebat). \ Annotated with PoS Labels by several undergraduates of the Sundanese Language Education Study Program (PPBS), UPI Bandung. """ _HOMEPAGE = "https://dataverse.telkomuniversity.ac.id/dataset.xhtml?persistentId=doi:10.34820/FK2/VTAHRH" _LICENSE = 'CC0 - "Public Domain Dedication"' _URLS = { _DATASETNAME: "https://dataverse.telkomuniversity.ac.id/api/access/datafile/:persistentId?persistentId=doi:10.34820/FK2/VTAHRH/WQIFK8", } _SUPPORTED_TASKS = [Tasks.POS_TAGGING] _SOURCE_VERSION = "1.1.0" _NUSANTARA_VERSION = "1.0.0" class PosSunMonoDataset(datasets.GeneratorBasedBuilder): """PoSTagged Sundanese Monolingual Corpus""" SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION) # Based on Wicaksono, A. F., & Purwarianti, A. (2010). HMM Based Part-of-Speech Tagger for Bahasa Indonesia. On Proceedings of 4th International MALINDO (Malay and Indonesian Language) Workshop. POS_TAGS = [ "", "!", '"', "'", ")", ",", "-", ".", "...", "....", "/", ":", ";", "?", "C", "CBI", "CC", "CDC", "CDI", "CDO", "CDP", "CDT", "CP", "CRB", "CS", "DC", "DT", "FE", "FW", "GM", "IN", "J", "JJ", "KA", "KK", "MD", "MG", "MN", "N", "NEG", "NN", "NNA", "NNG", "NNN", "NNO", "NNP", "NNPP", "NP", "NPP", "OP", "PB", "PCDP", "PR", "PRL", "PRL|IN", "PRN", "PRP", "RB", "RBT", "RB|RP", "RN", "RP", "SC", "SCC", "SC|IN", "SYM", "UH", "VB", "VBI", "VBT", "VRB", "W", "WH", "WHP", "WRP", "`", "–", "—", "‘", "’", "“", "”", ] BUILDER_CONFIGS = [ NusantaraConfig( name=f"{_DATASETNAME}_source", version=SOURCE_VERSION, description=f"{_DATASETNAME} source schema", schema="source", subset_id=f"{_DATASETNAME}", ), NusantaraConfig( name=f"{_DATASETNAME}_nusantara_seq_label", version=NUSANTARA_VERSION, description=f"{_DATASETNAME} Nusantara Seq Label schema", schema="nusantara_seq_label", subset_id=f"{_DATASETNAME}", ), ] DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source" def _info(self) -> datasets.DatasetInfo: if self.config.schema == "source": features = datasets.Features({"labeled_sentence": datasets.Value("string")}) elif self.config.schema == "nusantara_seq_label": features = schemas.seq_label_features(self.POS_TAGS) else: raise NotImplementedError(f"Schema '{self.config.schema}' is not defined.") return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: """Returns SplitGenerators.""" urls = _URLS[_DATASETNAME] data_path = dl_manager.download(urls) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "filepath": data_path, }, ), ] def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]: """Yields examples as (key, example) tuples.""" def __hotfix(line): if line.endswith(" taun|NN 1953.|."): return line.replace(" taun|NN 1953.|.", " taun|NN 1953|CDP .|.") elif line.endswith(" jeung|CC|CC sasab|RB .|."): return line.replace(" jeung|CC|CC sasab|RB .|.", " jeung|CC sasab|RB .|.") elif line.startswith("Kagiatan|NN éta|DT dihadiran|VBT kira|-kira "): return line.replace("Kagiatan|NN éta|DT dihadiran|VBT kira|-kira ", "Kagiatan|NN éta|DT dihadiran|VBT kira-kira|DT ") return line with open(filepath, "r", encoding="utf8") as ipt: raw = list(map(lambda l: __hotfix(l.rstrip("\n ")), ipt)) pat_0 = r"(,\|,|\?\|\?|-\|-|!\|!)" repl_spc = r" \1 " pat_1 = r"([A-Z”])(\.\|\.)" pat_2 = r"(\.\|\.)([^. ])" repl_spl = r"\1 \2" pat_3 = r"([^ ]+\|[^ ]+)\| " repl_del = r"\1 " pat_4 = r"\|\|" repl_dup = r"|" def __apply_regex(txt): for pat, repl in [(pat_0, repl_spc), (pat_1, repl_spl), (pat_2, repl_spl), (pat_3, repl_del), (pat_4, repl_dup)]: txt = re.sub(pat, repl, txt) return txt def __cleanse_label(token): text, label = token return text, re.sub(r"([A-Z]+)[.,)]", r"\1", label.upper()) if self.config.schema == "source": for key, example in enumerate(raw): yield key, {"labeled_sentence": example} elif self.config.schema == "nusantara_seq_label": spaced = list(map(__apply_regex, raw)) data = list(map(lambda l: [__cleanse_label(tok.split("|", 1)) for tok in filter(None, l.split(" "))], spaced)) for key, example in enumerate(data): tokens, labels = zip(*example) yield key, {"id": str(key), "tokens": tokens, "labels": labels} else: raise NotImplementedError(f"Schema '{self.config.schema}' is not defined.") if __name__ == "__main__": datasets.load_dataset(__file__)