Logical Inference on Dependency-based Compositional Semantics

Ran Tian, Yusuke Miyao, Takuya Matsuzaki

Abstract: Dependency-based Compositional Semantics (DCS) is a framework of natural language semantics with easy-to-process structures as well as strict semantics. In this paper, we equip the DCS framework with logical inference, by defining abstract denotations as an abstraction of the computing process of denotations in original DCS. An inference engine is built to achieve inference on abstract denotations. Furthermore, we propose a way to generate on-the-fly knowledge in logical inference, by combining our framework with the idea of tree transformation. Experiments on FraCaS and PASCAL RTE datasets show promising results.