Recognizing Implicit Discourse Relations through Abductive Reasoning with Large-scale Lexical Knowledge

Discourse relation recognition is the task of identifying the semantic relationships between textual units. Conventional approaches to discourse relation recognition exploit surface information and syntactic information as machine learning features. However, the performance of these models is severely limited for implicit discourse relation recognition. In this paper, we propose an abductive theorem proving (ATP) approach for implicit discourse relation recognition. The contribution of this paper is that we give a detailed discussion of an ATP-based discourse relation recognition model with open-domain web texts.