Datasets:
Multilinguality:
multilingual
Size Categories:
1M<n<10M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
ArXiv:
License:
cc-by-nc-sa-4.0
"""XL-Sum abstractive summarization dataset.""" | |
import json | |
import os | |
import datasets | |
_CITATION = """\ | |
@inproceedings{hasan-etal-2021-xl, | |
title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages", | |
author = "Hasan, Tahmid and | |
Bhattacharjee, Abhik and | |
Islam, Md. Saiful and | |
Mubasshir, Kazi and | |
Li, Yuan-Fang and | |
Kang, Yong-Bin and | |
Rahman, M. Sohel and | |
Shahriyar, Rifat", | |
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021", | |
month = aug, | |
year = "2021", | |
address = "Online", | |
publisher = "Association for Computational Linguistics", | |
url = "https://aclanthology.org/2021.findings-acl.413", | |
pages = "4693--4703", | |
} | |
""" | |
_DESCRIPTION = """\ | |
We present XLSum, a comprehensive and diverse dataset comprising 1.35 million professionally | |
annotated article-summary pairs from BBC, extracted using a set of carefully designed heuristics. | |
The dataset covers 45 languages ranging from low to high-resource, for many of which no | |
public dataset is currently available. XL-Sum is highly abstractive, concise, | |
and of high quality, as indicated by human and intrinsic evaluation. | |
""" | |
_HOMEPAGE = "https://github.com/csebuetnlp/xl-sum" | |
_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)" | |
_URL = "https://huggingface.co/datasets/csebuetnlp/xlsum/resolve/main/data/{}_XLSum_v{}.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 Xlsum(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("2.0.0") | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig( | |
name="{}".format(lang), | |
version=datasets.Version("2.0.0") | |
) | |
for lang in _LANGUAGES | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"url": datasets.Value("string"), | |
"title": 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_, { | |
"id": data["id"], | |
"url": data["url"], | |
"title": data["title"], | |
"summary": data["summary"], | |
"text": data["text"], | |
} | |