A Machine Learning Approach to Coreference Resolution of Noun Phrases

Wee Meng Soon, Hwee Tou Ng, Daniel Chung Yong Lim
2001 Computational Linguistics  
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, the
more » ... UC-6 and MUC-7 coreference corpora) and obtain encouraging results, indicating that on the general noun phrase coreference task, the learning approach holds promise and achieves accuracy comparable to that of nonlearning approaches. Our system is the first learning-based system that offers performance comparable to that of state-of-the-art nonlearning systems on these data sets.
doi:10.1162/089120101753342653 fatcat:ldyqgvih7ndqfilnbwfi5njumu