Standard pairwise coreference resolution systems are subject to errors resulting from their performing anaphora identification as an implicit part of coreference resolution. In this paper, we propose an integer linear programming (ILP) formulation for coreference resolution which models anaphoricity and coreference as a joint task, such that each local model informs the other for the final assignments. This joint ILP formulation provides fscore improvements of 3.7-5.3% over a base coreference classifier on the ACE datasets.
REF propose to use integer linear programming framework to model anaphoricity and coreference as a joint task.
Joint Determination of Anaphoricity and Coreference Resolution using Integer Programming
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference
Computer Science