Year: 2014
Type: conference-paper
Abstract: Text-level discourse parsing remains a challenge: most approaches employ features that fail to capture the intentional, semantic, and syntactic aspects that govern discourse coherence.In this paper, we propose a recursive model for discourse parsing that jointly models distributed representations for clauses, sentences, and entire discourses.The learned representations can to some extent learn the semantic and intentional import of words and larger discourse units automatically,.The proposed framework obtains comparable performance regarding standard discoursing parsing evaluations when compared against current state-of-art systems.
DOI: 10.3115/v1/d14-1220
Authors: Jiwei Li, Rumeng Li, Eduard Hovy
Institutions: Stanford University, Peking University, Carnegie Mellon University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2250767751