Inference Rules for Recognizing Textual Entailment

Abstract

In this paper, we explore the application of inference rules for recognizing textual entailment (RTE). We start with an automatically acquired collection and then propose methods to refine it and obtain more rules using a hand-crafted lexical resource. Following this, we derive a dependency-based representation from texts, which aims to provide a proper base for the inference rule application. The evaluation of our approach on the RTE data shows promising results on precision and the error analysis suggests future improvements.