Datasets:
Tasks:
Summarization
Multilinguality:
multilingual
Size Categories:
unknown
Language Creators:
unknown
Annotations Creators:
none
Source Datasets:
original
Tags:
License:
# 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. | |
"""WikiLingua: A benchmark dataset for multilingual abstractive summarization.""" | |
import os | |
import glob | |
import pickle | |
import datasets | |
_CITATION = """\ | |
@article{ladhak-wiki-2020, | |
title = {WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization}, | |
authors = {Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown}, | |
journal = {arXiv preprint arXiv:2010.03093}, | |
year = {2020}, | |
url = {https://arxiv.org/abs/2010.03093} | |
} | |
""" | |
_DESCRIPTION = """\ | |
WikiLingua is a large-scale multilingual dataset for the evaluation of | |
crosslingual abstractive summarization systems. The dataset includes ~770k | |
article and summary pairs in 18 languages from WikiHow. The gold-standard | |
article-summary alignments across languages was done by aligning the images | |
that are used to describe each how-to step in an article. | |
""" | |
_HOMEPAGE = "https://github.com/esdurmus/Wikilingua" | |
_LICENSE = "CC BY-NC-SA 3.0" | |
_URL = "wikilingua_cleaned.tar.gz" | |
VERSION = datasets.Version("2.0.0") | |
valid_language_codes = { | |
"ar", | |
"cs", | |
"de", | |
"en", | |
"es", | |
"fr", | |
"hi", | |
"id", | |
"it", | |
"ja", | |
"ko", | |
"nl", | |
"pt", | |
"ru", | |
"th", | |
"tr", | |
"vi", | |
"zh", | |
} | |
valid_config_names = ( | |
# multilingual | |
list(valid_language_codes) | |
+ [ | |
# crosslingual / bridge | |
f"{src}_{tgt}" | |
for src in valid_language_codes | |
for tgt in valid_language_codes | |
if src != tgt | |
] | |
# load all multilingual / all crosslingual | |
+ ["multilingual", "crosslingual"] | |
) | |
class WikilinguaModes: | |
MULTILINGUAL = "multilingual" # L -> L | |
CROSSLINGUAL = "crosslingual" # L1 -> L1, L2 -> L2, L1 -> L2, L2 -> L1 | |
BRIDGE = "bridge" # L -> en, en -> L, L -> L | |
class WikilinguaConfig(datasets.BuilderConfig): | |
"""BuilderConfig for WikiLingua.""" | |
def __init__(self, name, **kwargs): | |
""" | |
Args: | |
name (string): configuration name that indicates task setup and languages. | |
1. multilingual - <lang> | |
2. crosslingual - <lang1>_<lang2> | |
3. english as bridge - en_<lang> | |
4. load all multilingual - multilingual | |
5. load all crosslingual - crosslingual | |
lang refers to the respective two-letter language code. | |
note that the order of lang1/lang2 does not matter; | |
for language pair (L1, L2), we load L1 <-> L2 and L1 -> L1, L2 -> L2. | |
""" | |
if name not in valid_config_names: | |
raise ValueError( | |
f"Expected config name to be one of: {', '.join(valid_config_names)}" | |
) | |
eles = name.split("_") | |
if name in (WikilinguaModes.MULTILINGUAL, WikilinguaModes.CROSSLINGUAL): | |
self.mode = name | |
self.source_lang = None | |
self.target_lang = None | |
description = f"Wikilingua summarization data ({self.mode}; all instances)" | |
else: | |
if len(eles) == 1: | |
mode = WikilinguaModes.MULTILINGUAL | |
source_lang, target_lang = name, name | |
elif len(eles) == 2: | |
source_lang, target_lang = eles | |
if source_lang == "en" or target_lang == "en": | |
mode = WikilinguaModes.BRIDGE | |
else: | |
mode = WikilinguaModes.CROSSLINGUAL | |
self.source_lang = source_lang | |
self.target_lang = target_lang | |
self.mode = mode | |
description = ( | |
f"Wikilingua summarisation data ({mode}; {source_lang}, {target_lang})" | |
) | |
self.languages = set([self.source_lang, self.target_lang]) | |
super().__init__( | |
name=name, | |
description=description, | |
**kwargs, | |
) | |
class WikiLingua(datasets.GeneratorBasedBuilder): | |
"""WikiLingua: A benchmark dataset for multilingual abstractive summarization.""" | |
BUILDER_CONFIG_CLASS = WikilinguaConfig | |
BUILDER_CONFIGS = [ | |
WikilinguaConfig( | |
name=config_name, | |
version=VERSION, | |
) | |
for config_name in valid_config_names | |
] | |
DEFAULT_CONFIG_NAME = "en" | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"gem_id": datasets.Value("string"), | |
"gem_parent_id": datasets.Value("string"), | |
"source_language": datasets.Value("string"), | |
"target_language": datasets.Value("string"), | |
"source": datasets.Value("string"), | |
"target": datasets.Value("string"), | |
"references": [datasets.Value("string")], | |
} | |
), | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
dl_dir = dl_manager.download_and_extract(_URL) | |
data_dir = os.path.join(dl_dir, "cleaned") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepaths": glob.glob( | |
os.path.join(data_dir, f"wikilingua_*.train.pk") | |
) | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepaths": glob.glob( | |
os.path.join(data_dir, f"wikilingua_*lingual.val.pk") | |
) | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"filepaths": glob.glob( | |
os.path.join(data_dir, f"wikilingua_*lingual.test.pk") | |
) | |
}, | |
), | |
datasets.SplitGenerator( | |
name=f"sampled_{datasets.Split.VALIDATION}", | |
gen_kwargs={ | |
"filepaths": glob.glob( | |
os.path.join(data_dir, f"wikilingua_*_sampled.val.pk") | |
) | |
}, | |
), | |
datasets.SplitGenerator( | |
name=f"sampled_{datasets.Split.TEST}", | |
gen_kwargs={ | |
"filepaths": glob.glob( | |
os.path.join(data_dir, f"wikilingua_*_sampled.test.pk") | |
) | |
}, | |
), | |
] | |
def _generate_examples(self, filepaths): | |
"""Yields examples.""" | |
for filepath in filepaths: | |
if ( | |
self.config.name == WikilinguaModes.MULTILINGUAL | |
and WikilinguaModes.CROSSLINGUAL in filepath | |
) or ( | |
self.config.name == WikilinguaModes.CROSSLINGUAL | |
and WikilinguaModes.MULTILINGUAL in filepath | |
): | |
yield from [] | |
else: | |
with open(filepath, "rb") as f: | |
data = pickle.load(f) | |
for d in data: | |
idx = d["id"].replace(".", "-") | |
src = d["document"].strip() | |
tgt = d["summary"].strip() | |
src_lang = d["source"] | |
tgt_lang = d["target"] | |
# if loading specific language pair, filter for those | |
if any(self.config.languages): | |
if not ( | |
src_lang in self.config.languages | |
and tgt_lang in self.config.languages | |
): | |
continue | |
# in bridge, we are inerested in L <-> en and L -> L, but not en -> en | |
if self.config.mode == WikilinguaModes.BRIDGE: | |
if src_lang == "en" and tgt_lang == "en": | |
continue | |
yield idx, { | |
"gem_id": idx, | |
"gem_parent_id": idx, | |
"source_language": src_lang, | |
"target_language": tgt_lang, | |
"source": src, | |
"target": tgt, | |
"references": [tgt], | |
} | |