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A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution by Yang, Bishan; Cardie, Claire; Frazier, Peter is a scholarly article available to read on EtoBox.

What is A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution about?

We present a novel hierarchical distance-dependent Bayesian model for event coreference resolution. While existing generative models for event coreference resolution are completely unsupervised, our model allows for the incorporation of pairwise distances between event mentions -- information that is widely used in supervised coreference models to guide the generative clustering processing for better event clustering both within and across documents. We model the distances between event mentions using a feature-rich learnable distance function and encode them as Bayesian priors for nonparametric clustering. Experiments on the ECB+ corpus show that our model outperforms state-of-the-art methods for both within- and cross-document event coreference resolution.

Author

Yang, Bishan; Cardie, Claire; Frazier, Peter

Published

2015

Language

EN