Paper: Recursive Deep Models for Discourse Parsing

ACL ID D14-1220
Title Recursive Deep Models for Discourse Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014

Text-level discourse parsing remains a challenge: most approaches employ fea- tures that fail to capture the intentional, se- mantic, and syntactic aspects that govern discourse coherence. In this paper, we pro- pose a recursive model for discourse pars- ing that jointly models distributed repre- sentations for clauses, sentences, and en- tire discourses. The learned representa- tions can to some extent learn the seman- tic and intentional import of words and larger discourse units automatically,. The proposed framework obtains comparable performance regarding standard discours- ing parsing evaluations when compared against current state-of-art systems.