from pathlib import Path from typing import Dict, List, Tuple import datasets from nusacrowd.utils.configs import NusantaraConfig from nusacrowd.utils.constants import Tasks from nusacrowd.utils import schemas import pandas as pd _CITATION = """\ @INPROCEEDINGS{8629151, author={Aliyah Salsabila, Nikmatun and Ardhito Winatmoko, Yosef and Akbar Septiandri, Ali and Jamal, Ade}, booktitle={2018 International Conference on Asian Language Processing (IALP)}, title={Colloquial Indonesian Lexicon}, year={2018}, volume={}, number={}, pages={226-229}, doi={10.1109/IALP.2018.8629151}} """ _LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data) _LOCAL = False _DATASETNAME = "kamus_alay" _DESCRIPTION = """\ Kamus Alay provide a lexicon for text normalization of Indonesian colloquial words. It contains 3,592 unique colloquial words-also known as “bahasa alay” -and manually annotated them with the normalized form. We built this lexicon from Instagram comments provided by Septiandri & Wibisono (2017) """ _HOMEPAGE = "https://ieeexplore.ieee.org/abstract/document/8629151" _LICENSE = "Unknown" _URLS = { _DATASETNAME: "https://raw.githubusercontent.com/nasalsabila/kamus-alay/master/colloquial-indonesian-lexicon.csv", } _SUPPORTED_TASKS = [Tasks.MORPHOLOGICAL_INFLECTION] # Dataset does not have versioning _SOURCE_VERSION = "1.0.0" _NUSANTARA_VERSION = "1.0.0" class KamusAlay(datasets.GeneratorBasedBuilder): """Kamus Alay is a dataset of lexicon for text normalization of Indonesian colloquial word""" SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION) label_classes = [ "abreviasi", "afiksasi", "akronim", "anaptiksis", "coinage", "elongasi", "homofon", "metatesis", "modifikasi vokal", "monoftongisasi", "naturalisasi", "pungtuasi", "reduplikasi", "salah ketik", "subtitusi", "word-value letter", "zeroisasi", ] BUILDER_CONFIGS = [ NusantaraConfig( name="kamus_alay_source", version=SOURCE_VERSION, description="Kamus Alay source schema", schema="source", subset_id="kamus_alay", ), NusantaraConfig( name="kamus_alay_nusantara_pairs_multi", version=NUSANTARA_VERSION, description="Kamus Alay Nusantara schema", schema="nusantara_pairs_multi", subset_id="kamus_alay", ), ] DEFAULT_CONFIG_NAME = "kamus_alay_source" def _info(self) -> datasets.DatasetInfo: if self.config.schema == "source": features = datasets.Features( { "slang": datasets.Value("string"), "formal": datasets.Value("string"), "in_dictionary": datasets.Value("bool"), "context": datasets.Value("string"), "categories": datasets.Sequence(datasets.Value("string")), } ) elif self.config.schema == "nusantara_pairs_multi": features = schemas.pairs_multi_features(self.label_classes) 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_dir = Path(dl_manager.download(urls)) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "filepath": data_dir, "split": "train", }, ), ] def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]: """Yields examples as (key, example) tuples.""" # Dataset does not have id, using row index as id df = pd.read_csv(filepath, encoding="ISO-8859-1").reset_index() df.columns = ["id", "slang", "formal", "is_in_dictionary", "example", "category1", "category2", "category3"] if self.config.schema == "source": for row in df.itertuples(): ex = { "slang": row.slang, "formal": row.formal, "in_dictionary": row.is_in_dictionary, "context": row.example, "categories": [c for c in (row.category1, row.category2, row.category3) if c != "0"], } yield row.id, ex elif self.config.schema == "nusantara_pairs_multi": for row in df.itertuples(): ex = { "id": str(row.id), "text_1": row.formal, "text_2": row.slang, "label": [c for c in (row.category1, row.category2, row.category3) if c != "0"], } yield row.id, ex else: raise ValueError(f"Invalid config: {self.config.name}")