Datasets:

cfilt
/

HiNER-collapsed

	import os

	import datasets
	from typing import List
	import json

	logger = datasets.logging.get_logger(__name__)


	_CITATION = """
	XX
	"""

	_DESCRIPTION = """
	This is the repository for HiNER - a large Hindi Named Entity Recognition dataset.
	"""

	class HiNERCollapsedConfig(datasets.BuilderConfig):
	"""BuilderConfig for Conll2003"""

	def __init__(self, **kwargs):
	"""BuilderConfig forConll2003.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(HiNERCollapsedConfig, self).__init__(**kwargs)


	class HiNERCollapsedConfig(datasets.GeneratorBasedBuilder):
	"""HiNER Collapsed dataset."""

	BUILDER_CONFIGS = [
	HiNERCollapsedConfig(name="HiNER-Collapsed", version=datasets.Version("0.0.2"), description="Hindi Named Entity Recognition Dataset"),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"tokens": datasets.Sequence(datasets.Value("string")),
	"ner_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-PERSON",
	"I-PERSON",
	"B-LOCATION",
	"I-LOCATION",
	"B-ORGANIZATION",
	"I-ORGANIZATION"
	]
	)
	),
	}
	),
	supervised_keys=None,
	homepage="YY",
	citation=_CITATION,
	)

	_URL = "https://huggingface.co/datasets/cfilt/HiNER-collapsed/resolve/main/data/"
	_URLS = {
	"train": _URL + "train.json",
	"validation": _URL + "validation.json",
	"test": _URL + "test.json"
	}

	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
	urls_to_download = self._URLS
	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["validation"]}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
	]

	def _generate_examples(self, filepath):
	"""This function returns the examples in the raw (text) form."""
	logger.info("⏳ Generating examples from = %s", filepath)
	with open(filepath) as f:
	data = json.load(f)
	for object in data:
	id_ = int(object['id'])
	yield id_, {
	"id": str(id_),
	"tokens": object['tokens'],
	#"pos_tags": object['pos_tags'],
	"ner_tags": object['ner_tags'],
	}
	# 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("\t")
	# tokens.append(splits[0].strip())
	# # pos_tags.append(splits[1])
	# # chunk_tags.append(splits[2])
	# ner_tags.append(splits[1].rstrip())
	# # last example
	# yield guid, {
	# "id": str(guid),
	# "tokens": tokens,
	# # "pos_tags": pos_tags,
	# # "chunk_tags": chunk_tags,
	# "ner_tags": ner_tags,
	# }