Normalized Alignment of Dependency Trees for Detecting Textual Entailment
published: Feb. 25, 2007, recorded: April 2006, views: 2963
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In this paper, we investigate the usefulness of normalized alignment of dependency trees for entailment prediction. Overall, our approach yields an accuracy of 60% on the RTE2 test set, which is a significant improvement over the baseline. Results vary substantially across the different subsets, with a peak performance on the summarization data. We conclude that normalized alignment is useful for detecting textual entailment, but a robust approach will probably need to include additional sources of information.
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