Datasets:
Multilinguality:
translation
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1K<n<10K
Source Datasets:
extended|other-wikimatrix
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# 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(" ")],
}
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