Papers › CSD: A Chinese Dataset for Subtext Problem

CSD: A Chinese Dataset for Subtext Problem

16 Jan 2022ACL ARR January 2022 1archive 2025-07-28

Anonymous

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.

PaperPDFCode

Code

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections