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A Machine Learning Approach to Coreference Resolution of Noun Phrases
In this paper, we present a learning approach to coreference resolution of noun phrases in unrestricted text. The approach learns from a small, annotated corpus and the task includes resolving not just a certain type of noun phrase (e.g., pronouns) but rather general noun phrases. It also does not restrict the entity types of the noun phrases; that is, coreference is assigned whether they are of "organization," "person," or other types. We evaluate our approach on common data sets (namely, thedoi:10.1162/089120101753342653 fatcat:ldyqgvih7ndqfilnbwfi5njumu