Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution
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.
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Clusteringcoreference-resolutionCoreference ResolutionEvent Coreference ResolutionSimilar Papers 제목 키워드 기반
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