import datasets import os logger = datasets.logging.get_logger(__name__) _URL = "https://raw.githubusercontent.com/Kriyansparsana/demorepo/main/train.txt" class indian_namesConfig(datasets.BuilderConfig): """The WNUT 17 Emerging Entities Dataset.""" def __init__(self, **kwargs): """BuilderConfig for WNUT 17. Args: **kwargs: keyword arguments forwarded to super. """ super(indian_namesConfig, self).__init__(**kwargs) class indian_names(datasets.GeneratorBasedBuilder): """The WNUT 17 Emerging Entities Dataset.""" BUILDER_CONFIGS = [ indian_namesConfig( name="indian_names", version=datasets.Version("1.0.0"), description="The WNUT 17 Emerging Entities Dataset" ), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("string"), "tokens": datasets.Sequence(datasets.Value("string")), "pos_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ '"', "''", "#", "$", "(", ")", ",", ".", ":", "``", "CC", "CD", "DT", "EX", "FW", "IN", "JJ", "JJR", "JJS", "LS", "MD", "NN", "NNP", "NNPS", "NNS", "NN|SYM", "PDT", "POS", "PRP", "PRP$", "RB", "RBR", "RBS", "RP", "SYM", "TO", "UH", "VB", "VBD", "VBG", "VBN", "VBP", "VBZ", "WDT", "WP", "WP$", "WRB", ] ) ), "chunk_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-ADJP", "I-ADJP", "B-ADVP", "I-ADVP", "B-CONJP", "I-CONJP", "B-INTJ", "I-INTJ", "B-LST", "I-LST", "B-NP", "I-NP", "B-PP", "I-PP", "B-PRT", "I-PRT", "B-SBAR", "I-SBAR", "B-UCP", "I-UCP", "B-VP", "I-VP", ] ) ), "ner_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC", ] ) ), } ), supervised_keys=None, homepage="https://www.aclweb.org/anthology/W03-0419/", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" downloaded_file = dl_manager.download_and_extract(_URL) data_files = { "train": os.path.join(downloaded_file, _TRAINING_FILE), "dev": os.path.join(downloaded_file, _DEV_FILE), "test": os.path.join(downloaded_file, _TEST_FILE), } return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}), ] def _generate_examples(self, filepath): logger.info("⏳ Generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as f: guid = 0 tokens = [] pos_tags = [] chunk_tags = [] ner_tags = [] for line in f: if line.startswith("-DOCSTART-") or line == "" or line == "\n": if tokens: yield guid, { "id": str(guid), "tokens": tokens, "pos_tags": pos_tags, "chunk_tags": chunk_tags, "ner_tags": ner_tags, } guid += 1 tokens = [] pos_tags = [] chunk_tags = [] ner_tags = [] else: # conll2003 tokens are space separated splits = line.split(" ") tokens.append(splits[0]) pos_tags.append(splits[1]) chunk_tags.append(splits[2]) ner_tags.append(splits[3].rstrip()) # last example if tokens: yield guid, { "id": str(guid), "tokens": tokens, "pos_tags": pos_tags, "chunk_tags": chunk_tags, "ner_tags": ner_tags, }