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User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization

2021-04-08NAACL 2021Code Available0· sign in to hype

Shohei Higashiyama, Masao Utiyama, Taro Watanabe, Eiichiro Sumita

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Abstract

Morphological analysis (MA) and lexical normalization (LN) are both important tasks for Japanese user-generated text (UGT). To evaluate and compare different MA/LN systems, we have constructed a publicly available Japanese UGT corpus. Our corpus comprises 929 sentences annotated with morphological and normalization information, along with category information we classified for frequent UGT-specific phenomena. Experiments on the corpus demonstrated the low performance of existing MA/LN methods for non-general words and non-standard forms, indicating that the corpus would be a challenging benchmark for further research on UGT.

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