  No neural coreference resolver for Arabic exists, in fact we are not aware of
any learning-based coreference resolver for Arabic since (Bjorkelund and Kuhn,
2014). In this paper, we introduce a coreference resolution system for Arabic
based on Lee et al's end to end architecture combined with the Arabic version
of bert and an external mention detector. As far as we know, this is the first
neural coreference resolution system aimed specifically to Arabic, and it
substantially outperforms the existing state of the art on OntoNotes 5.0 with a
gain of 15.2 points conll F1. We also discuss the current limitations of the
task for Arabic and possible approaches that can tackle these challenges.
