Datasets:
yahoo_answers_qa

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors.
	#
	# 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.
	"""Yahoo Non-Factoid Question Dataset"""


	import json
	import os

	import datasets


	logger = datasets.logging.get_logger(__name__)


	_DESCRIPTION = """\
	Yahoo Non-Factoid Question Dataset is derived from Yahoo's Webscope L6 collection using machine learning techiques such \
	that the questions would contain non-factoid answers.The dataset contains 87,361 questions and their corresponding answers. \
	Each question contains its best answer along with additional other answers submitted by users. \
	Only the best answer was reviewed in determining the quality of the question-answer pair.
	"""

	_URL = "https://ciir.cs.umass.edu/downloads/nfL6/nfL6.json.gz"


	class YahooAnswersQa(datasets.GeneratorBasedBuilder):
	"""Yahoo Non-Factoid Question Dataset"""

	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIGS = [datasets.BuilderConfig(name="yahoo_answers_qa", version=datasets.Version("1.0.0"))]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"question": datasets.Value("string"),
	"answer": datasets.Value("string"),
	"nbestanswers": datasets.features.Sequence(datasets.Value("string")),
	"main_category": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	homepage="https://ciir.cs.umass.edu/downloads/nfL6/index.html",
	)

	def _split_generators(self, dl_manager):
	downloaded_file = dl_manager.download_and_extract(_URL)
	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
	]

	def _generate_examples(self, filepath):
	logger.info("⏳ Generating examples from = %s", filepath)
	if os.path.isdir(filepath):
	filepath = os.path.join(filepath, "nfL6.json")
	with open(filepath, encoding="utf-8") as f:
	data = json.load(f)
	for example in data:
	yield example["id"], example