{"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/csd-a-chinese-dataset-for-subtext-problem","title":"CSD: A Chinese Dataset for Subtext Problem","arxiv_id":null,"date":"2022-01-16","proceeding":"ACL ARR January 2022 1","authors":["Anonymous"],"abstract":"Subtext is a kind of deep semantics which can be acquired after one or more rounds of expression transformation. As a popular way of expressing one's intentions, it is well worth studying. In this paper, we propose two subtext-related tasks which are termed ``subtext recognition'' and ``subtext recovery'' and make a clear definition for their purposes. Moreover, we build a Chinese dataset whose source data comes from popular social media (e.g. Weibo, Netease Music, Zhihu, and Bilibili) and propose a new evaluation metric termed ``Two-stages Annotation Evaluation'' (TAE) for the validation of a multi-turn annotation process.","url_abs":"https://openreview.net/forum?id=C1NSnnXEMuU","url_pdf":"https://openreview.net/pdf?id=C1NSnnXEMuU","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":"csd-a-chinese-dataset-for-subtext-problem","repo_url":"https://github.com/MindSpore-scientific/code-12/tree/main/CSD","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}