{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/user-generated-text-corpus-for-evaluating","title":"User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization","arxiv_id":"2104.03523","date":"2021-04-08","proceeding":"NAACL 2021 4","authors":["Shohei Higashiyama","Masao Utiyama","Taro Watanabe","Eiichiro Sumita"],"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.","url_abs":"https://arxiv.org/abs/2104.03523v1","url_pdf":"https://arxiv.org/pdf/2104.03523v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"user-generated-text-corpus-for-evaluating","repo_url":"https://github.com/shigashiyama/jlexnorm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"lexical-normalization","task_name":"Lexical Normalization"},{"task_slug":"morphological-analysis","task_name":"Morphological Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2104.03523","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}