In this paper, we introduce a new framework for recognizing textual entailment (RTE) which depends on extraction of the set of publicly-held beliefs -known as discourse commitments -that can be ascribed to the author of a text (t) or a hypothesis (h). We show that once a set of commitments have been extracted from a t-h pair, the task of recognizing textual entailment is reduced to the identification of the commitments from a t which support the inference of the h. Our system correctly identified entailment relationships in more than 80% of t-h pairs taken from all three of the previous PASCAL RTE Challenges, without the need for additional sources of training data.
Additionally, work in textual entailment has used discourse commitments, which are general beliefs held by the author of the text and hypothesis REF .
Using Discourse Commitments to Recognize Textual Entailment
International Conference On Computational Linguistics
Computer Science