Normalized Alignment of Dependency Trees for Detecting Textual Entailment


Marsi, E. and Krahmer, E. and Bosma, W.E. and Theune, M. (2006) Normalized Alignment of Dependency Trees for Detecting Textual Entailment. In: Second PASCAL Recognising Textual Entailment Challenge, 10-12 April 2006, Venice, Italy (pp. pp. 56-61).

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Abstract: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 entailments, but a robust approach will probably need to include additional sources of information.
Item Type:Conference or Workshop Item
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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