A CCG-based Compositional Semantics and Inference System for Comparatives
This addresses a gap in computational semantics for natural language inference, though it appears incremental as it builds on existing CCG frameworks.
The paper tackles the problem of representing and reasoning with comparative constructions in natural language by developing a CCG-based compositional semantics and inference system, showing it can handle various complex logical inferences on the FraCaS test suite.
Comparative constructions play an important role in natural language inference. However, attempts to study semantic representations and logical inferences for comparatives from the computational perspective are not well developed, due to the complexity of their syntactic structures and inference patterns. In this study, using a framework based on Combinatory Categorial Grammar (CCG), we present a compositional semantics that maps various comparative constructions in English to semantic representations and introduces an inference system that effectively handles logical inference with comparatives, including those involving numeral adjectives, antonyms, and quantification. We evaluate the performance of our system on the FraCaS test suite and show that the system can handle a variety of complex logical inferences with comparatives.