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