Normalized alignment of dependency trees for detecting textual entailment
Erwin Marsi, Emiel Krahmer, Wauter Bosma, Mariët Theune · University of Twente Research Information · 2006
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. 1