Coreference Resolution with and without Linguistic Knowledge
نویسنده
چکیده
State-of-the-art statistical approaches to the Coreference Resolution task rely on sophisticated modeling, but very few (10-20) simple features. In this paper we propose to extend the standard feature set substantially, incorporating more linguistic knowledge. To investigate the usability of linguistically motivated features, we evaluate our system for a variety of machine learners on the standard dataset (MUC7) with the traditional learning set-up (Soon et al., 2001).
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