Datasets:
Modalities:
Text
Formats:
parquet
Sub-tasks:
semantic-similarity-classification
Size:
1M - 10M
Tags:
paraphrase-generation
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. | |
"""TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages""" | |
import csv | |
import os | |
import datasets | |
_CITATION = """\ | |
@dataset{scherrer_yves_2020_3707949, | |
author = {Scherrer, Yves}, | |
title = {{TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages}}, | |
month = mar, | |
year = 2020, | |
publisher = {Zenodo}, | |
version = {1.0}, | |
doi = {10.5281/zenodo.3707949}, | |
url = {https://doi.org/10.5281/zenodo.3707949} | |
} | |
""" | |
_DESCRIPTION = """\ | |
A freely available paraphrase corpus for 73 languages extracted from the Tatoeba database. \ | |
Tatoeba is a crowdsourcing project mainly geared towards language learners. Its aim is to provide example sentences \ | |
and translations for particular linguistic constructions and words. The paraphrase corpus is created by populating a \ | |
graph with Tatoeba sentences and equivalence links between sentences “meaning the same thing”. This graph is then \ | |
traversed to extract sets of paraphrases. Several language-independent filters and pruning steps are applied to \ | |
remove uninteresting sentences. A manual evaluation performed on three languages shows that between half and three \ | |
quarters of inferred paraphrases are correct and that most remaining ones are either correct but trivial, \ | |
or near-paraphrases that neutralize a morphological distinction. The corpus contains a total of 1.9 million \ | |
sentences, with 200 – 250 000 sentences per language. It covers a range of languages for which, to our knowledge,\ | |
no other paraphrase dataset exists.""" | |
_HOMEPAGE = "https://zenodo.org/record/3707949#.X9Dh0cYza3I" | |
_LICENSE = "Creative Commons Attribution 2.0 Generic" | |
_URLs = { | |
"train": "https://zenodo.org/record/3707949/files/tapaco_v1.0.zip?download=1", | |
} | |
_VERSION = "1.0.0" | |
_LANGUAGES = { | |
"af": "Afrikaans", | |
"ar": "Arabic", | |
"az": "Azerbaijani", | |
"be": "Belarusian", | |
"ber": "Berber languages", | |
"bg": "Bulgarian", | |
"bn": "Bengali", | |
"br": "Breton", | |
"ca": "Catalan; Valencian", | |
"cbk": "Chavacano", | |
"cmn": "Mandarin", | |
"cs": "Czech", | |
"da": "Danish", | |
"de": "German", | |
"el": "Greek, Modern (1453-)", | |
"en": "English", | |
"eo": "Esperanto", | |
"es": "Spanish; Castilian", | |
"et": "Estonian", | |
"eu": "Basque", | |
"fi": "Finnish", | |
"fr": "French", | |
"gl": "Galician", | |
"gos": "Gronings", | |
"he": "Hebrew", | |
"hi": "Hindi", | |
"hr": "Croatian", | |
"hu": "Hungarian", | |
"hy": "Armenian", | |
"ia": "Interlingua (International Auxiliary Language Association)", | |
"id": "Indonesian", | |
"ie": "Interlingue; Occidental", | |
"io": "Ido", | |
"is": "Icelandic", | |
"it": "Italian", | |
"ja": "Japanese", | |
"jbo": "Lojban", | |
"kab": "Kabyle", | |
"ko": "Korean", | |
"kw": "Cornish", | |
"la": "Latin", | |
"lfn": "Lingua Franca Nova\t", | |
"lt": "Lithuanian", | |
"mk": "Macedonian", | |
"mr": "Marathi", | |
"nb": "Bokmål, Norwegian; Norwegian Bokmål", | |
"nds": "Low German; Low Saxon; German, Low; Saxon, Low", | |
"nl": "Dutch; Flemish", | |
"orv": "Old Russian", | |
"ota": "Turkish, Ottoman (1500-1928)", | |
"pes": "Iranian Persian", | |
"pl": "Polish", | |
"pt": "Portuguese", | |
"rn": "Rundi", | |
"ro": "Romanian; Moldavian; Moldovan", | |
"ru": "Russian", | |
"sl": "Slovenian", | |
"sr": "Serbian", | |
"sv": "Swedish", | |
"tk": "Turkmen", | |
"tl": "Tagalog", | |
"tlh": "Klingon; tlhIngan-Hol", | |
"toki": "Toki Pona", | |
"tr": "Turkish", | |
"tt": "Tatar", | |
"ug": "Uighur; Uyghur", | |
"uk": "Ukrainian", | |
"ur": "Urdu", | |
"vi": "Vietnamese", | |
"vo": "Volapük", | |
"war": "Waray", | |
"wuu": "Wu Chinese", | |
"yue": "Yue Chinese", | |
} | |
_ALL_LANGUAGES = "all_languages" | |
class TapacoConfig(datasets.BuilderConfig): | |
"""BuilderConfig for TapacoConfig.""" | |
def __init__(self, languages=None, **kwargs): | |
super(TapacoConfig, self).__init__(version=datasets.Version(_VERSION, ""), **kwargs), | |
self.languages = languages | |
class Tapaco(datasets.GeneratorBasedBuilder): | |
BUILDER_CONFIGS = [ | |
TapacoConfig( | |
name=_ALL_LANGUAGES, | |
languages=_LANGUAGES, | |
description="A collection of paraphrase corpus for 73 languages to aid paraphrase " | |
"detection and generation.", | |
) | |
] + [ | |
TapacoConfig( | |
name=lang, | |
languages=[lang], | |
description=f"{_LANGUAGES[lang]} A collection of paraphrase corpus for 73 languages to " | |
f"aid paraphrase " | |
"detection and generation.", | |
) | |
for lang in _LANGUAGES | |
] | |
BUILDER_CONFIG_CLASS = TapacoConfig | |
DEFAULT_CONFIG_NAME = _ALL_LANGUAGES | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"paraphrase_set_id": datasets.Value("string"), | |
"sentence_id": datasets.Value("string"), | |
"paraphrase": datasets.Value("string"), | |
"lists": datasets.Sequence(datasets.Value("string")), | |
"tags": datasets.Sequence(datasets.Value("string")), | |
"language": datasets.Value("string"), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
data_dir = dl_manager.download_and_extract(_URLs) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={"data_dir": data_dir["train"]}, | |
), | |
] | |
def _generate_examples(self, data_dir): | |
"""Yields examples.""" | |
base_path = os.path.join(data_dir, "tapaco_v1.0") | |
file_dict = {lang: os.path.join(base_path, lang + ".txt") for lang in self.config.languages} | |
id_ = -1 | |
for language, filepath in file_dict.items(): | |
with open(filepath, encoding="utf-8") as csv_file: | |
csv_reader = csv.reader( | |
csv_file, quotechar='"', delimiter="\t", quoting=csv.QUOTE_ALL, skipinitialspace=True | |
) | |
for row in csv_reader: | |
id_ += 1 | |
paraphrase_set_id, sentence_id, paraphrase, lists, tags = row[: len(row)] + [""] * (5 - len(row)) | |
yield id_, { | |
"paraphrase_set_id": paraphrase_set_id, | |
"sentence_id": sentence_id, | |
"paraphrase": paraphrase, | |
"lists": lists.split(";"), | |
"tags": tags.split(";"), | |
"language": language, | |
} | |