Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser

Abstract

This paper presents a system that compositionally maps outputs of a wide-coverage Japanese CCG parser onto semantic representations and performs automated inference in higher-order logic. The system is evaluated on a textual entailment dataset. It is shown that the system solves inference problems that focus on a variety of complex linguistic phenomena, including those that are difficult to represent in the standard first-order logic.