The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity

Abstract

Shared Task 1 of SemEval-2014 com-prised two subtasks on the same dataset of sentence pairs: recognizing textual en-tailment and determining textual similar-ity. We used an existing system based on formal semantics and logical inference to participate in the first subtask, reaching an accuracy of 82%, ranking in the top 5 of more than twenty participating sys-tems. For determining semantic similar-ity we took a supervised approach using a variety of features, the majority of which was produced by our system for recogniz-ing textual entailment. In this subtask our system achieved a mean squared error of 0.322, the best of all participating systems. 1