Going beyond <cite>Iida et al. (2011)</cite> , our model computes a resolution hypothesis incrementally; for the performance of this aspect of the system we followed previously used metrics for evaluation : first correct: how deep into the RE does the model predict the referent for the first time? first final: how deep into the RE does the model predict the correct referent and keep that decision until the end? edit overhead: how often did the model unnecessarily change its prediction (the only necessary prediction happens when it first makes a correct prediction)?