Inference rules for recognizing textual entailment

In this paper, we explore the application of inference rules for recogniz-ing textual entailment (RTE). We start with an automatically acquired col-lection 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 in-ference rule application. The evaluation of our approach on the RTE data shows promising results on precision and the error analysis suggests future improvements.