Datasets:
Tasks:
Summarization
Sub-tasks:
news-articles-summarization
Multilinguality:
multilingual
Size Categories:
1M<n<10M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
ArXiv:
License:
"""CrossSum cross-lingual abstractive summarization dataset.""" | |
import json | |
import os | |
import datasets | |
_CITATION = """\ | |
@article{hasan2021crosssum, | |
author = {Tahmid Hasan and Abhik Bhattacharjee and Wasi Uddin Ahmad and Yuan-Fang Li and Yong-bin Kang and Rifat Shahriyar}, | |
title = {CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs}, | |
journal = {CoRR}, | |
volume = {abs/2112.08804}, | |
year = {2021}, | |
url = {https://arxiv.org/abs/2112.08804}, | |
eprinttype = {arXiv}, | |
eprint = {2112.08804} | |
} | |
""" | |
_DESCRIPTION = """\ | |
We present CrossSum, a large-scale dataset | |
comprising 1.70 million cross-lingual article summary samples in 1500+ language-pairs | |
constituting 45 languages. We use the multilingual XL-Sum dataset and align identical | |
articles written in different languages via crosslingual retrieval using a language-agnostic | |
representation model. | |
""" | |
_HOMEPAGE = "https://github.com/csebuetnlp/CrossSum" | |
_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)" | |
_URL = "https://huggingface.co/datasets/csebuetnlp/CrossSum/resolve/main/data/{}-{}_CrossSum.tar.bz2" | |
_LANGUAGES = [ | |
"oromo", | |
"french", | |
"amharic", | |
"arabic", | |
"azerbaijani", | |
"bengali", | |
"burmese", | |
"chinese_simplified", | |
"chinese_traditional", | |
"welsh", | |
"english", | |
"kirundi", | |
"gujarati", | |
"hausa", | |
"hindi", | |
"igbo", | |
"indonesian", | |
"japanese", | |
"korean", | |
"kyrgyz", | |
"marathi", | |
"spanish", | |
"scottish_gaelic", | |
"nepali", | |
"pashto", | |
"persian", | |
"pidgin", | |
"portuguese", | |
"punjabi", | |
"russian", | |
"serbian_cyrillic", | |
"serbian_latin", | |
"sinhala", | |
"somali", | |
"swahili", | |
"tamil", | |
"telugu", | |
"thai", | |
"tigrinya", | |
"turkish", | |
"ukrainian", | |
"urdu", | |
"uzbek", | |
"vietnamese", | |
"yoruba", | |
] | |
class Crosssum(datasets.GeneratorBasedBuilder): | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig( | |
name="{}-{}".format(src_lang, tgt_lang), | |
version=datasets.Version("1.0.0") | |
) | |
for src_lang in _LANGUAGES | |
for tgt_lang in _LANGUAGES | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"source_url": datasets.Value("string"), | |
"target_url": datasets.Value("string"), | |
"summary": datasets.Value("string"), | |
"text": datasets.Value("string"), | |
} | |
), | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
citation=_CITATION, | |
license=_LICENSE, | |
version=self.VERSION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
lang = str(self.config.name) | |
url = _URL.format(lang, self.VERSION.version_str[:-2]) | |
data_dir = dl_manager.download_and_extract(url) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, lang + "_train.jsonl"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, lang + "_test.jsonl"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, lang + "_val.jsonl"), | |
}, | |
), | |
] | |
def _generate_examples(self, filepath): | |
"""Yields examples as (key, example) tuples.""" | |
with open(filepath, encoding="utf-8") as f: | |
for idx_, row in enumerate(f): | |
data = json.loads(row) | |
yield idx_, { | |
"source_url": data["source_url"], | |
"target_url": data["target_url"], | |
"summary": data["summary"], | |
"text": data["text"], | |
} | |