Learning Alignments and Leveraging Natural Logic

Citation

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.

Abstract

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.


Read more from SRI

  • surgeons around a surgical robot

    The SRI research behind today’s surgical robotics

    Intuitive’s da Vinci 5 system represents a major leap in robotic-assisted medicine. It all started at SRI, which continues to advance teleoperation technologies.

  • a collage of digital graphs

    A banner year for quantum

    SRI-managed QED-C’s annual report on quantum trends captures an industry accelerating rapidly from technical promise toward major global impact.

  • ICE Cube containing SRI’s aerogel experiment, photographed prior to launch. Source: Aerospace Applications North America

    An SRI carbon capture experiment launches into space

    By synthesizing carbon-absorbing aerogels in microgravity, SRI research will give us a rare glimpse into how these materials could be radically improved.