import json import os import datasets logger = datasets.logging.get_logger(__name__) _CITATION = """\ """ _DESCRIPTION = """\ """ _HOMEPAGE = "https://indicnlp.ai4bharat.org/" _LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License" _URL = "https://huggingface.co/datasets/ai4bharat/naamapadam/resolve/main/data/{}_IndicNER_v{}.zip" _LANGUAGES = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"] class Naamapadam(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ datasets.BuilderConfig( name="{}".format(lang), version=datasets.Version("1.0.0") ) for lang in _LANGUAGES ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "tokens": datasets.Sequence(datasets.Value("string")), "tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", ] ) ), } ), supervised_keys=None, homepage=_HOMEPAGE, citation=_CITATION, license=_LICENSE, version=self.VERSION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" lang = str(self.config.name) url = _URL.format(lang, self.VERSION.version_str[:-2]) data_dir = dl_manager.download_and_extract(url) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "filepath": os.path.join(data_dir, lang + "_train.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "filepath": os.path.join(data_dir, lang + "_test.json"), }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "filepath": os.path.join(data_dir, lang + "_val.json"), }, ), ] def _generate_examples(self, filepath): logger.info(f"generating examples from = {filepath}") """Yields examples as (key, example) tuples.""" with open(filepath, encoding="utf-8") as f: for idx_, row in enumerate(f): data = json.loads(row) yield idx_, {"tokens": data["words"], "tags": data["ner"]}