Title

Dependency-based textual entailment

Abstract

This paper studies the role of dependency information for the task of textual entailment. Both the Text and Hypothesis of an entailment pair are mapped into sets of dependencies and a score is computed that measures the similarity of the two sets. Based on the score an entailment decision is made. Two experiments are conducted to measure the impact of dependencies on the entailment task. In one experiment we compare the dependency-based approach with a baseline approach on a standard data set. In a second experiment, we measure the performance on a subset of the standard data set. The subset is so selected to minimize the effect of other factors, such as word-level information, in the performance measurement process. A brief discussion compares the dependency-based approach to other, similar approaches. Copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.

Publication Title

FLAIRS 2006 - Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference

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