We argue that, with appropriate modification to the learning instances, local training is adequate for the coreference resolution task.
we propose that confusing pairs in the training data -such as "she" and "Elizabeth (1) " -be learned as notcoreferent, so long as the global inference step can fix this error by exploiting the structure of the output space, i.e.