Probabilistic Resolution of Anaphoric Reference

John Burger and Dennis Conolly

This paper describes the use of a Bayesian network to resolve anaphora by probabilistically combining linguistic evidence. By adopting a Bayesian approach, we are able to combine diverse evidence in a principled way, extend current understanding of linguistic phenomena by quantifying relationships empirically, and better model the non-deterministic role of linguistic evidence in resolution of anaphora. We also briefly discuss our current research into the use of learning techniques to automatically construct Bayesian networks from data.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.