Learning Alignments and Leveraging Natural Logic


Chambers Nathanael, Cer Daniel, Grenager Trond, Hall David, Kiddon Chloe, MacCartney Bill, De Marneffe Marie-Catherine, Ramage Daniel, Yeh Eric, Manning Christopher D. Learning alignments and leveraging natural logic, in Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pp. 165-170, 2007.


We describe an approach to textual inference that improves alignments at both the typed dependency level and at a deeper semantic level. We present a machine learning approach to alignment scoring, a stochastic search procedure, and a new tool that finds deeper semantic alignments, allowing rapid development of semantic features over the aligned graphs. Further, we describe a complementary semantic component based on natural logic, which shows an added gain of 3.13% accuracy on the RTE3 test set.

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