Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution

Part of Advances in Neural Information Processing Systems 22 (NIPS 2009)

Bibtex Metadata Paper


Cosmin Bejan, Matthew Titsworth, Andrew Hickl, Sanda Harabagiu


We present a sequence of unsupervised, nonparametric Bayesian models for clustering complex linguistic objects. In this approach, we consider a potentially infinite number of features and categorical outcomes. We evaluate these models for the task of within- and cross-document event coreference on two corpora. All the models we investigated show significant improvements when compared against an existing baseline for this task.