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        <title>A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution</title>
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    <name type="personal">
        <namePart type="given">Bishan</namePart>
        <namePart type="family">Yang</namePart>
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    <name type="personal">
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    <abstract>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.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00155</identifier>
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        <date>2015</date>
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%0 Journal Article
%T A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution
%A Yang, Bishan
%A Cardie, Claire
%A Frazier, Peter
%J Transactions of the Association for Computational Linguistics
%D 2015
%V 3
%I MIT Press
%C Cambridge, MA
%F yang-etal-2015-hierarchical
%X 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.
%R 10.1162/tacl_a_00155
%U https://aclanthology.org/Q15-1037
%U https://doi.org/10.1162/tacl_a_00155
%P 517-528

Markdown (Informal)

[A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution](https://aclanthology.org/Q15-1037) (Yang et al., TACL 2015)

• A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution (Yang et al., TACL 2015)

ACL

• Bishan Yang, Claire Cardie, and Peter Frazier. 2015. A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution. Transactions of the Association for Computational Linguistics, 3:517–528.