Datasets:
refresd

	# 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.
	"""The Rationalized English-French Semantic Divergences (REFreSD) dataset."""


	import csv

	import datasets


	_CITATION = """\
	@inproceedings{briakou-carpuat-2020-detecting,
	title = "Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank",
	author = "Briakou, Eleftheria and Carpuat, Marine",
	booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
	month = nov,
	year = "2020",
	address = "Online",
	publisher = "Association for Computational Linguistics",
	url = "https://www.aclweb.org/anthology/2020.emnlp-main.121",
	pages = "1563--1580",
	}
	"""

	_DESCRIPTION = """\
	The Rationalized English-French Semantic Divergences (REFreSD) dataset consists of 1,039
	English-French sentence-pairs annotated with sentence-level divergence judgments and token-level
	rationales. For any questions, write to ebriakou@cs.umd.edu.
	"""

	_HOMEPAGE = "https://github.com/Elbria/xling-SemDiv/tree/master/REFreSD"

	_LICENSE = "MIT"

	_URL = "https://raw.githubusercontent.com/Elbria/xling-SemDiv/master/REFreSD/REFreSD_rationale"


	class Refresd(datasets.GeneratorBasedBuilder):
	"""The Rationalized English-French Semantic Divergences (REFreSD) dataset."""

	VERSION = datasets.Version("1.1.0")

	def _info(self):
	features = datasets.Features(
	{
	"sentence_pair": datasets.Translation(languages=["en", "fr"]),
	"label": datasets.features.ClassLabel(names=["divergent", "equivalent"]),
	"all_labels": datasets.features.ClassLabel(
	names=["unrelated", "some_meaning_difference", "no_meaning_difference"]
	),
	"rationale_en": datasets.features.Sequence(datasets.Value("int32")),
	"rationale_fr": datasets.features.Sequence(datasets.Value("int32")),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

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

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
	for idx, row in enumerate(reader):
	yield idx, {
	"sentence_pair": {"fr": row["#french_sentence"], "en": row["#english_sentence"]},
	"label": row["#binary_label"],
	"all_labels": row["#3_labels"],
	"rationale_en": [int(v) for v in row["#english_rational"].split(" ")],
	"rationale_fr": [int(v) for v in row["#french_rationale"].split(" ")],
	}