import json import pandas as pd import datasets logger = datasets.logging.get_logger(__name__) _DESCRIPTION = """\ Klue Relation Extraction Data """ _URL = "https://huggingface.co/datasets/LeverageX/klue-re/resolve/main/" _URLS = { "train_data": _URL + "klue-re-v1.1_train.json", "validation_data": _URL + "klue-re-v1.1_dev.json", } class KoreanNewspaper(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ datasets.BuilderConfig( name="KLUE Relation Extraction", version=datasets.Version("1.0.0", ""), description="For LeverageX Project", ), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "guid": datasets.Value("string"), "label": datasets.Value("string"), "object_entity": datasets.Value("String"), "sentencce": datasets.Value("string"), "source": datasets.Value("string"), "subject_entity": datasets.Value("string"), } ), # No default supervised_keys (as we have to pass both question # and context as input). supervised_keys=None, homepage="https://klue-benchmark.com/tasks/70/overview/description", ) def _split_generators(self, dl_manager): downloaded_files = dl_manager.download_and_extract(_URLS) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" logger.info("generating examples from = %s", filepath) key = 0 with open(filepath, encoding="utf-8") as f : data = json.load(f) for info in data : guid = info['guid'] label = info['label'] object_entity = info['object_entity'] subject_entity = info['subject_entity'] source = info['source'] yield key, { "guid" : guid, "label" : label, "object_entity" : object_entity, "subject_entity" : subject_entity, "source" : source, } key += 1