Datasets:
time_dial

	# 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.
	"""Temporal Commonsense Reasoning in Dialog"""


	import json

	import datasets


	_CITATION = """\
	@inproceedings{qin-etal-2021-timedial,
	title = "{TimeDial: Temporal Commonsense Reasoning in Dialog}",
	author = "Qin, Lianhui and Gupta, Aditya and Upadhyay, Shyam and He, Luheng and Choi, Yejin and Faruqui, Manaal",
	booktitle = "Proc. of ACL",
	year = "2021"
	}
	"""

	_DESCRIPTION = """\
	TimeDial presents a crowdsourced English challenge set, for temporal commonsense reasoning, formulated
	as a multiple choice cloze task with around 1.5k carefully curated dialogs. The dataset is derived from
	the DailyDialog (Li et al., 2017), which is a multi-turn dialog corpus.

	In order to establish strong baselines and provide information on future model development, we
	conducted extensive experiments with state-of-the-art LMs. While humans can easily answer these
	questions (97.8%), the best T5 model variant struggles on this challenge set (73%). Moreover, our
	qualitative error analyses show that the models often rely on shallow, spurious features (particularly text
	matching), instead of truly doing reasoning over the context.
	"""

	_HOMEPAGE = "https://github.com/google-research-datasets/timedial"

	_LICENSE = "TimeDial dataset is licensed under CC BY-NC-SA 4.0"

	_URL = "https://raw.githubusercontent.com/google-research-datasets/TimeDial/main/test.json"


	class TimeDial(datasets.GeneratorBasedBuilder):
	"""Temporal Commonsense Reasoning in Dialog"""

	VERSION = datasets.Version("1.1.0")

	def _info(self):
	features = datasets.Features(
	{
	"id": datasets.Value("int32"),
	"conversation": datasets.features.Sequence(datasets.Value("string")),
	"correct1": datasets.Value("string"),
	"correct2": datasets.Value("string"),
	"incorrect1": datasets.Value("string"),
	"incorrect1_rule": datasets.Value("string"),
	"incorrect2": datasets.Value("string"),
	"incorrect2_rule": datasets.Value("string"),
	}
	)
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage=_HOMEPAGE,
	# License for the dataset if available
	license=_LICENSE,
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": dl_manager.download_and_extract(_URL), "split": "test"},
	),
	]

	def _generate_examples(
	self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	):
	"""Yields examples as (key, example) tuples."""

	with open(filepath, encoding="utf-8") as f:
	glob_id = 0
	row = json.load(f)
	for data in row:
	yield glob_id, {
	"id": data["id"],
	"conversation": data["conversation"],
	"correct1": data["correct1"],
	"correct2": data["correct2"],
	"incorrect1": data["incorrect1"],
	"incorrect1_rule": data["incorrect1_rule"],
	"incorrect2": data["incorrect2"],
	"incorrect2_rule": data["incorrect2_rule"],
	}
	glob_id += 1