Neural Coreference Resolution for Arabic

• URL: http://arxiv.org/abs/2011.00286v1
• Date: Sat, 31 Oct 2020 14:34:43 GMT
• Title: Neural Coreference Resolution for Arabic
• Authors: Abdulrahman Aloraini, Juntao Yu and Massimo Poesio
• Abstract summary: 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. It substantially outperforms the existing state of the art on OntoNotes 5.0 with a gain of 15.2 points conll F1.
• Score: 12.986359659930146
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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