Optimization in coreference resolution is not needed
Manfred Klenner, Étienne Ailloud · 2009
We show how global constraints such as transitivity can be treated intensionally in a Zero-One Integer Linear Programming (ILP) framework which is geared to find the optimal and coherent partition of coreference sets given a number of candidate pairs and their weights delivered by a pairwise classifier (used as reliable clustering seed pairs). In order to find out whether ILP optimization, which is NP-complete, actually is the best we can do, we compared the first consistent solution generated by our adaptation of an efficient Zero-One algorithm with the optimal solution. The first consistent solution, which often can be found very fast, is already as good as the optimal solution; optimization is thus not needed.