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postag_su / postag_su.py
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# 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 seacrowd.utils import schemas
from seacrowd.utils.configs import SEACrowdConfig
from seacrowd.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"
_SEACROWD_VERSION = "2024.06.20"
class PosSunMonoDataset(datasets.GeneratorBasedBuilder):
"""PoSTagged Sundanese Monolingual Corpus"""
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
SEACROWD_VERSION = datasets.Version(_SEACROWD_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 = [
SEACrowdConfig(
name=f"{_DATASETNAME}_source",
version=SOURCE_VERSION,
description=f"{_DATASETNAME} source schema",
schema="source",
subset_id=f"{_DATASETNAME}",
),
SEACrowdConfig(
name=f"{_DATASETNAME}_seacrowd_seq_label",
version=SEACROWD_VERSION,
description=f"{_DATASETNAME} Nusantara Seq Label schema",
schema="seacrowd_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 == "seacrowd_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 == "seacrowd_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.")