A Logic Prover Approach to Predicting Textual Similarity

This paper presents a logic prover approach to predicting textual similarity. Sentences are represented using three logic forms capturing different levels of knowledge, from only content words to semantic representations extracted with an existing semantic parser. A logic prover is used to find proofs and derive semantic features that are combined in a machine learning framework. Experimental results show that incorporating the semantic structure of sentences yields better results than simpler pairwise word similarity measures.