Motivated in part by these recently developed models, we propose in this paper a clusterranking approach to coreference resolution that combines the strengths of mention-ranking mod-els and entity-mention models.
we recast coreference as the problem of determining which of a set of preceding coreference clusters is the best to link to an active mention using a learned cluster ranker.