Natural Language Inference with CCG Parser and Automated Theorem Prover for DTS

Asa Tomita, Mai Matsubara, Hinari Daido, Daisuke Bekki

We propose a Natural Language Inference (NLI) system based on compositional semantics. The system combines lightblue, a syntactic and semantic parser grounded in Combinatory Categorial Grammar (CCG) and Dependent Type Semantics (DTS), with Wani, an automated theorem prover for Dependent Type Theory (DTT). Because each computational step reflects a theoretical assumption, system evaluation serves as a form of hypothesis verification. We evaluate the inference system using the Japanese Semantic Test Suite JSeM, and demonstrate how error analysis provides feedback to improve both the system and the underlying linguistic theory.