Inference Rules and their Application to Recognizing Textual Entailment

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