Learning-based Multi-Sieve Co-reference Resolution with Knowledge

Sieve-based Coreference Resolution in the Biomedical Domain

We describe challenges and advantages unique to coreference resolution in the biomedical domain, and a sieve-based architecture that leverages domain knowledge for both entity and event coreference resolution. Domain-gen…

A Multi-Pass Sieve Coreference Resolution for Indonesian

Coreference resolution is an NLP task to find out whether the set of referring expressions belong to the same concept in discourse. A multi-pass sieve is a deterministic coreference model that implements several layers o…

Event Coreference Resolution with Multi-Pass Sieves

Multi-pass sieve approaches have been successfully applied to entity coreference resolution and many other tasks in natural language processing (NLP), owing in part to the ease of designing high-precision rules for these…

Joint Coreference Resolution and Named-Entity Linking with Multi-Pass Sieves

A hybrid entity-centric approach to Persian pronoun resolution

Pronoun resolution is a challenging subset of an essential field in natural language processing called coreference resolution. Coreference resolution is about finding all entities in the text that refers to the same real…