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Liputan6: A Large-scale Indonesian Dataset for Text Summarization

2020-11-02 02:01:12
Fajri Koto, Jey Han Lau, Timothy Baldwin
arXiv_CL
         
Abstract

In this paper, we introduce a large-scale Indonesian summarization dataset. We harvest articles from this http URL, an online news portal, and obtain 215,827 document-summary pairs. We leverage pre-trained language models to develop benchmark extractive and abstractive summarization methods over the dataset with multilingual and monolingual BERT-based models. We include a thorough error analysis by examining machine-generated summaries that have low ROUGE scores, and expose both issues with ROUGE it-self, as well as with extractive and abstractive summarization models.

Abstract (translated)

URL

https://arxiv.org/abs/2011.00679

PDF

https://arxiv.org/pdf/2011.00679.pdf

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