from pathlib import Path from typing import Dict, List, Tuple import datasets import pandas as pd from nusacrowd.utils import schemas from nusacrowd.utils.configs import NusantaraConfig from nusacrowd.utils.constants import Tasks _CITATION = """ """ _DATASETNAME = "id_sts" _DESCRIPTION = """\ SemEval is a series of international natural language processing (NLP) research workshops whose mission is to advance the current state of the art in semantic analysis and to help create high-quality annotated datasets in a range of increasingly challenging problems in natural language semantics. This is a translated version of SemEval Dataset from 2012-2016 for Semantic Textual Similarity Task to Indonesian language. """ _HOMEPAGE = "https://github.com/ahmadizzan/sts-indo" _LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data) _LOCAL = False _LICENSE = "Unknown" _URLS = { _DATASETNAME: { "train": "https://raw.githubusercontent.com/ahmadizzan/sts-indo/master/data/final-data/train.tsv", "test": "https://raw.githubusercontent.com/ahmadizzan/sts-indo/master/data/final-data/test.tsv", } } _SUPPORTED_TASKS = [Tasks.SEMANTIC_SIMILARITY] _SOURCE_VERSION = "1.0.0" _NUSANTARA_VERSION = "1.0.0" class IdSts(datasets.GeneratorBasedBuilder): """id_sts, translated version of SemEval Dataset from 2012-2016 for Semantic Textual Similarity Task to Indonesian language""" SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION) BUILDER_CONFIGS = [ NusantaraConfig( name="id_sts_source", version=SOURCE_VERSION, description="ID_STS source schema", schema="source", subset_id="id_sts", ), NusantaraConfig( name="id_sts_nusantara_pairs_score", version=NUSANTARA_VERSION, description="ID_STS Nusantara schema", schema="nusantara_pairs_score", subset_id="id_sts", ), ] DEFAULT_CONFIG_NAME = "id_sts_source" def _info(self) -> datasets.DatasetInfo: if self.config.schema == "source": features = datasets.Features( { "text_1": datasets.Value("string"), "text_2": datasets.Value("string"), "label": datasets.Value("float64"), } ) elif self.config.schema == "nusantara_pairs_score": features = schemas.pairs_features_score() return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: urls = _URLS[_DATASETNAME] train_data_path = Path(dl_manager.download(urls["train"])) test_data_path = Path(dl_manager.download(urls["test"])) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_data_path, "split": "train"}, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={"filepath": test_data_path, "split": "test"}, ), ] 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, delimiter="\t").reset_index() df.columns = ["id", "score", "original_text_1", "original_text_2", "source", "text_1", "text_2"] if self.config.schema == "source": for row in df.itertuples(): ex = {"text_1": row.text_1, "text_2": row.text_2, "label": row.score} yield row.id, ex elif self.config.schema == "nusantara_pairs_score": for row in df.itertuples(): ex = {"id": str(row.id), "text_1": row.text_1, "text_2": row.text_2, "label": row.score} yield row.id, ex else: raise ValueError(f"Invalid config: {self.config.name}")