Recursive Deep Models for Discourse Parsing

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. 1