import os from typing import Dict, List, Tuple try: from typing import Literal, TypedDict except ImportError: from typing_extensions import Literal, TypedDict import datasets from nusacrowd.utils import schemas from nusacrowd.utils.configs import NusantaraConfig from nusacrowd.utils.constants import Tasks _CITATION = """\ @inproceedings{id_panl_bppt, author = {PAN Localization - BPPT}, title = {Parallel Text Corpora, English Indonesian}, year = {2009}, url = {http://digilib.bppt.go.id/sampul/p92-budiono.pdf}, } """ _LOCAL = False _LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data) _DATASETNAME = "id_panl_bppt" _DESCRIPTION = """\ Parallel Text Corpora for Multi-Domain Translation System created by BPPT (Indonesian Agency for the Assessment and Application of Technology) for PAN Localization Project (A Regional Initiative to Develop Local Language Computing Capacity in Asia). The dataset contains about 24K sentences in English and Bahasa Indonesia from 4 different topics (Economy, International Affairs, Science & Technology, and Sports). """ _HOMEPAGE = "http://digilib.bppt.go.id/sampul/p92-budiono.pdf" _LICENSE = "" _URLS = { _DATASETNAME: "https://github.com/cahya-wirawan/indonesian-language-models/raw/master/data/BPPTIndToEngCorpusHalfM.zip", } _SUPPORTED_TASKS = [Tasks.MACHINE_TRANSLATION] # Source has no versioning _SOURCE_VERSION = "1.0.0" _NUSANTARA_VERSION = "1.0.0" class IdPanlBppt(datasets.GeneratorBasedBuilder): """\ Dataset contains about ~24K sentences in English and Bahasa Indonesia from 4 different topics (Economy, International Affairs, Science & Technology, and Sports) """ SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION) class Topic(TypedDict): name: Literal["Economy", "International", "Science", "Sport"] # seems to be the number of words in the file words: Literal["150K", "100K"] TOPICS: List[Topic] = [{"name": "Economy", "words": "150K"}, {"name": "International", "words": "150K"}, {"name": "Science", "words": "100K"}, {"name": "Sport", "words": "100K"}] SOURCE_LANGUAGE = "en" TARGET_LANGUAGE = "id" BUILDER_CONFIGS = [ NusantaraConfig( name="id_panl_bppt_source", version=SOURCE_VERSION, description="PANL BPPT source schema", schema="source", subset_id="id_panl_bppt", ), NusantaraConfig( name="id_panl_bppt_nusantara_t2t", version=NUSANTARA_VERSION, description="PANL BPPT Nusantara schema", schema="nusantara_t2t", subset_id="id_panl_bppt", ), ] DEFAULT_CONFIG_NAME = "id_panl_bppt_source" def _info(self) -> datasets.DatasetInfo: if self.config.schema == "source": features = datasets.Features( { "id": datasets.Value("string"), "translation": datasets.features.Translation(languages=[self.SOURCE_LANGUAGE, self.TARGET_LANGUAGE]), "topic": datasets.features.ClassLabel(names=list(map(lambda topic: topic["name"], self.TOPICS))), } ) elif self.config.schema == "nusantara_t2t": features = schemas.text2text_features 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 = dl_manager.download_and_extract(urls) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "dir": os.path.join(data_dir, "plain"), "split": "train", }, ), ] def _generate_examples(self, dir: str, split: str) -> Tuple[int, Dict]: """Yields examples as (key, example) tuples.""" id = 0 for topic in self.TOPICS: src_path = f"PANL-BPPT-{topic['name'][:3].upper()}-{self.SOURCE_LANGUAGE.upper()}-{topic['words']}w.txt" tgt_path = f"PANL-BPPT-{topic['name'][:3].upper()}-{self.TARGET_LANGUAGE.upper()}-{topic['words']}w.txt" with open(os.path.join(dir, src_path), encoding="utf-8") as f1, open(os.path.join(dir, tgt_path), encoding="utf-8") as f2: src = f1.read().split("\n")[:-1] tgt = f2.read().split("\n")[:-1] for s, t in zip(src, tgt): if self.config.schema == "source": yield id, { "id": str(id), "translation": {self.SOURCE_LANGUAGE: s, self.TARGET_LANGUAGE: t}, "topic": topic["name"], } elif self.config.schema == "nusantara_t2t": # Schema does not have topics or any other fields to have the topics yield id, { "id": str(id), "text_1": s, "text_2": t, "text_1_name": self.SOURCE_LANGUAGE, "text_2_name": self.TARGET_LANGUAGE, } id += 1