Litcius/Paper detail

Cross-document Coreference Resolution over Predicted Mentions

Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

202127 citationsDOIOpen Access PDF

Abstract

Coreference resolution has been mostly investigated within a single document scope, showing impressive progress in recent years based on end-to-end models.However, the more challenging task of cross-document (CD) coreference resolution remained relatively under-explored, with the few recent models applied only to gold mentions.Here, we introduce the first end-to-end model for CD coreference resolution from raw text, which extends the prominent model for withindocument coreference to the CD setting.Our model achieves competitive results for event and entity coreference resolution on gold mentions.More importantly, we set first baseline results, on the standard ECB+ dataset, for CD coreference resolution over predicted mentions.Further, our model is simpler and more efficient than recent CD coreference resolution systems, while not using any external resources. 1

Topics & Concepts

CoreferenceComputer scienceResolution (logic)Natural language processingScope (computer science)Artificial intelligenceSet (abstract data type)Task (project management)Event (particle physics)Programming languageEconomicsQuantum mechanicsManagementPhysicsTopic ModelingNatural Language Processing TechniquesBiomedical Text Mining and Ontologies