import datasets logger = datasets.logging.get_logger(__name__) _URL = "https://raw.githubusercontent.com/Kriyansparsana/demorepo/main/" _TRAINING_FILE = "wnut17train%20(1).conll" _DEV_FILE = "indian_ner_dev.conll" _TEST_FILE = "indian_ner_test.conll" 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( features=datasets.Features( { "id": datasets.Value("string"), "tokens": datasets.Sequence(datasets.Value("string")), "ner_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-corporation", "I-corporation", "B-person", "I-person", ] ) ), } ), supervised_keys=None, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" urls_to_download = { "train": f"{_URL}{_TRAINING_FILE}", "dev": f"{_URL}{_DEV_FILE}", "test": f"{_URL}{_TEST_FILE}", } downloaded_files = dl_manager.download_and_extract(urls_to_download) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), ] def _generate_examples(self, filepath): logger.info("⏳ Generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as f: current_tokens = [] current_labels = [] sentence_counter = 0 for row in f: row = row.rstrip() if row: if "\t" in row: token, label = row.split("\t") current_tokens.append(token) current_labels.append(label) else: # Handle cases where the delimiter is missing # You can choose to skip these rows or handle them differently logger.warning(f"Delimiter missing in row: {row}") else: # New sentence if not current_tokens: # Consecutive empty lines will cause empty sentences continue assert len(current_tokens) == len(current_labels), "💔 between len of tokens & labels" sentence = ( sentence_counter, { "id": str(sentence_counter), "tokens": current_tokens, "ner_tags": current_labels, }, ) sentence_counter += 1 current_tokens = [] current_labels = [] yield sentence # Don't forget the last sentence in the dataset 🧐 if current_tokens: yield sentence_counter, { "id": str(sentence_counter), "tokens": current_tokens, "ner_tags": current_labels, }