Paper: Unsupervised Event Coreference Resolution with Rich Linguistic Features

ACL ID P10-1143
Title Unsupervised Event Coreference Resolution with Rich Linguistic Features
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

This paper examines how a new class of nonparametric Bayesian models can be ef- fectively applied to an open-domain event coreference task. Designed with the pur- pose of clustering complex linguistic ob- jects, these models consider a potentially infinite number of features and categorical outcomes. The evaluation performed for solving both within- and cross-document event coreference shows significant im- provements of the models when compared against two baselines for this task.