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Upload postag_su.py with huggingface_hub
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postag_su.py
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# coding=utf-8
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# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import re
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from pathlib import Path
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from typing import Dict, List, Tuple
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import datasets
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from nusacrowd.utils import schemas
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from nusacrowd.utils.configs import NusantaraConfig
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from nusacrowd.utils.constants import Tasks
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_CITATION = """\
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@data{FK2/VTAHRH_2022,
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author = {ARDIYANTI SURYANI, ARIE and Widyantoro, Dwi Hendratmo and Purwarianti, Ayu and Sudaryat, Yayat},
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publisher = {Telkom University Dataverse},
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title = {{PoSTagged Sundanese Monolingual Corpus}},
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year = {2022},
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version = {DRAFT VERSION},
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doi = {10.34820/FK2/VTAHRH},
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url = {https://doi.org/10.34820/FK2/VTAHRH}
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}
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@INPROCEEDINGS{7437678,
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author={Suryani, Arie Ardiyanti and Widyantoro, Dwi Hendratmo and Purwarianti, Ayu and Sudaryat, Yayat},
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booktitle={2015 International Conference on Information Technology Systems and Innovation (ICITSI)},
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title={Experiment on a phrase-based statistical machine translation using PoS Tag information for Sundanese into Indonesian},
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year={2015},
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volume={},
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number={},
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pages={1-6},
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doi={10.1109/ICITSI.2015.7437678}
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}
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"""
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_LANGUAGES = ["sun"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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_LOCAL = False
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_DATASETNAME = "postag_su"
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_DESCRIPTION = """\
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This dataset contains 3616 lines of Sundanese sentences taken from several online magazines (Mangle, Dewan Dakwah Jabar, and Balebat). \
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Annotated with PoS Labels by several undergraduates of the Sundanese Language Education Study Program (PPBS), UPI Bandung.
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"""
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_HOMEPAGE = "https://dataverse.telkomuniversity.ac.id/dataset.xhtml?persistentId=doi:10.34820/FK2/VTAHRH"
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_LICENSE = 'CC0 - "Public Domain Dedication"'
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_URLS = {
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_DATASETNAME: "https://dataverse.telkomuniversity.ac.id/api/access/datafile/:persistentId?persistentId=doi:10.34820/FK2/VTAHRH/WQIFK8",
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}
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_SUPPORTED_TASKS = [Tasks.POS_TAGGING]
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_SOURCE_VERSION = "1.1.0"
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_NUSANTARA_VERSION = "1.0.0"
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class PosSunMonoDataset(datasets.GeneratorBasedBuilder):
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"""PoSTagged Sundanese Monolingual Corpus"""
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
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# 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.
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POS_TAGS = [
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"",
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"!",
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'"',
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"'",
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")",
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",",
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"-",
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".",
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"...",
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"....",
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"/",
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":",
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";",
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"?",
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"C",
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"CBI",
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"CC",
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"CDC",
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"CDI",
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"CDO",
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"CDP",
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"CDT",
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"CP",
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"CRB",
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"CS",
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"DC",
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"DT",
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"FE",
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"FW",
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"GM",
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"IN",
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"J",
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"JJ",
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"KA",
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"KK",
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"MD",
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"MG",
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"MN",
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"N",
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"NEG",
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"NN",
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"NNA",
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"NNG",
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"NNN",
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"NNO",
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"NNP",
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"NNPP",
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"NP",
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"NPP",
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"OP",
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"PB",
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"PCDP",
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"PR",
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"PRL",
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"PRL|IN",
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"PRN",
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"PRP",
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"RB",
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"RBT",
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"RB|RP",
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"RN",
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"RP",
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"SC",
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"SCC",
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"SC|IN",
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"SYM",
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"UH",
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"VB",
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"VBI",
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"VBT",
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"VRB",
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"W",
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"WH",
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"WHP",
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"WRP",
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"`",
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"–",
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"—",
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"‘",
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"’",
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"“",
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"”",
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]
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BUILDER_CONFIGS = [
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NusantaraConfig(
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name=f"{_DATASETNAME}_source",
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version=SOURCE_VERSION,
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description=f"{_DATASETNAME} source schema",
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schema="source",
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subset_id=f"{_DATASETNAME}",
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),
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NusantaraConfig(
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name=f"{_DATASETNAME}_nusantara_seq_label",
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version=NUSANTARA_VERSION,
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description=f"{_DATASETNAME} Nusantara Seq Label schema",
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schema="nusantara_seq_label",
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subset_id=f"{_DATASETNAME}",
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),
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]
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DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
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def _info(self) -> datasets.DatasetInfo:
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if self.config.schema == "source":
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features = datasets.Features({"labeled_sentence": datasets.Value("string")})
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elif self.config.schema == "nusantara_seq_label":
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features = schemas.seq_label_features(self.POS_TAGS)
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else:
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raise NotImplementedError(f"Schema '{self.config.schema}' is not defined.")
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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"""Returns SplitGenerators."""
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urls = _URLS[_DATASETNAME]
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data_path = dl_manager.download(urls)
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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={
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"filepath": data_path,
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},
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),
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]
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def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
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"""Yields examples as (key, example) tuples."""
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def __hotfix(line):
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if line.endswith(" taun|NN 1953.|."):
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return line.replace(" taun|NN 1953.|.", " taun|NN 1953|CDP .|.")
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elif line.endswith(" jeung|CC|CC sasab|RB .|."):
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return line.replace(" jeung|CC|CC sasab|RB .|.", " jeung|CC sasab|RB .|.")
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elif line.startswith("Kagiatan|NN éta|DT dihadiran|VBT kira|-kira "):
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return line.replace("Kagiatan|NN éta|DT dihadiran|VBT kira|-kira ", "Kagiatan|NN éta|DT dihadiran|VBT kira-kira|DT ")
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return line
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with open(filepath, "r", encoding="utf8") as ipt:
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raw = list(map(lambda l: __hotfix(l.rstrip("\n ")), ipt))
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pat_0 = r"(,\|,|\?\|\?|-\|-|!\|!)"
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repl_spc = r" \1 "
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pat_1 = r"([A-Z”])(\.\|\.)"
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pat_2 = r"(\.\|\.)([^. ])"
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repl_spl = r"\1 \2"
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pat_3 = r"([^ ]+\|[^ ]+)\| "
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repl_del = r"\1 "
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+
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pat_4 = r"\|\|"
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repl_dup = r"|"
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+
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def __apply_regex(txt):
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for pat, repl in [(pat_0, repl_spc), (pat_1, repl_spl), (pat_2, repl_spl), (pat_3, repl_del), (pat_4, repl_dup)]:
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txt = re.sub(pat, repl, txt)
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return txt
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+
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def __cleanse_label(token):
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text, label = token
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return text, re.sub(r"([A-Z]+)[.,)]", r"\1", label.upper())
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+
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if self.config.schema == "source":
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for key, example in enumerate(raw):
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yield key, {"labeled_sentence": example}
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+
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elif self.config.schema == "nusantara_seq_label":
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spaced = list(map(__apply_regex, raw))
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data = list(map(lambda l: [__cleanse_label(tok.split("|", 1)) for tok in filter(None, l.split(" "))], spaced))
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+
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for key, example in enumerate(data):
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tokens, labels = zip(*example)
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yield key, {"id": str(key), "tokens": tokens, "labels": labels}
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+
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else:
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raise NotImplementedError(f"Schema '{self.config.schema}' is not defined.")
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+
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+
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if __name__ == "__main__":
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datasets.load_dataset(__file__)
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