Natural language inference with monotonicity

Abstract

This paper describes a working system which performs natural language inference using polarity-marked parse trees. The system handles all of the instances of monotonicity inference in the FraCaS data set, and can be easily extended to compute inferences in other sections of FraCaS. We achieve perfect precision and an accuracy comparable to previous systems on the first section of FraCaS. Except for the initial parse, it is entirely deterministic. It handles multi-premise arguments. The kind of inference performed is essentially “logical”, but it goes beyond what is representable in first-order logic. In any case, the system works on surface forms and CCG parse trees rather than on logical representations of any kind.