We have examined two largely unexplored issues in computing and using anaphoricity information for improving learning-based coreference systems: representation and optimization.
we have systematically evaluated all four combinations of local vs. global optimization and constraint-based vs. feature-based representation of anaphoricity information in terms of their effectiveness in improving a learning-based coreference system.