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Evaluating the Impact of a Hierarchical Discourse Representation on Entity Coreference Resolution Performance

تقييم تأثير تمثيل الخطاب التسلسل الهرمي حول أداء دقة كائن كوراسة

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 Publication date 2021
and research's language is English
 Created by Shamra Editor




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Recent work on entity coreference resolution (CR) follows current trends in Deep Learning applied to embeddings and relatively simple task-related features. SOTA models do not make use of hierarchical representations of discourse structure. In this work, we leverage automatically constructed discourse parse trees within a neural approach and demonstrate a significant improvement on two benchmark entity coreference-resolution datasets. We explore how the impact varies depending upon the type of mention.



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