We present an approach to pronoun resolution based on syntactic paths. Through a simple bootstrapping procedure, we learn the likelihood of coreference between a pronoun and a candidate noun based on the path in the parse tree between the two entities. This path information enables us to handle previously challenging resolution instances, and also robustly addresses traditional syntactic coreference constraints. Highly coreferent paths also allow mining of precise probabilistic gender/number information. We combine statistical knowledge with well known features in a Support Vector Machine pronoun resolution classifier. Significant gains in performance are observed on several datasets.
REF determine the likelihood of coreference along the syntactic path connecting a pronoun to a possible antecedent, by looking at the distribution of the path in text.
Bootstrapping Path-Based Pronoun Resolution
International Conference On Computational Linguistics And Annual Meeting Of The Association For Computational Linguistics
Computer Science