Datasets:
kor_qpair

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	"""Korean pairwise question binary classification dataset"""


	import datasets


	_CITATION = """\
	@misc{Song:2018,
	title = "Paired Question v.2",
	authors = "Youngsook Song",
	publisher = "GitHub",
	year = "2018"
	}
	"""


	_DESCRIPTION = """\
	This is a Korean paired question dataset containing labels indicating whether two questions in a given pair are semantically identical. This dataset was used to evaluate the performance of [KoGPT2](https://github.com/SKT-AI/KoGPT2#subtask-evaluations) on a phrase detection downstream task.
	"""


	_HOMEPAGE = "https://github.com/songys/Question_pair"

	_LICENSE = "The MIT License (MIT)"

	_URL = "https://raw.githubusercontent.com/songys/Question_pair/master/"
	_URLs = {key: f"{_URL}{key}.txt" for key in ("train", "test", "validation")}


	class KorQpair(datasets.GeneratorBasedBuilder):
	"""Korean pairwise question classification dataset"""

	VERSION = datasets.Version("1.1.0")

	def _info(self):

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"question1": datasets.Value("string"),
	"question2": datasets.Value("string"),
	"is_duplicate": datasets.ClassLabel(names=["0", "1"]),
	}
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	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"],
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": downloaded_files["test"],
	"split": "test",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": downloaded_files["validation"],
	"split": "validation",
	},
	),
	]

	def _generate_examples(self, filepath, split):
	with open(filepath, encoding="utf-8") as f:
	next(f)
	for id_, row in enumerate(f):
	row = row.strip().split("\t")
	yield id_, {
	"question1": row[0],
	"question2": row[1],
	"is_duplicate": row[2],
	}