State-of-the-art NLP approaches to coreference resolution: theory and practical recipes

Authors:
Simone Paolo Ponzetto;Massimo Poesio
Affiliations:
University of Heidelberg;University of Trento
Venue:
ACLTutorials '09 Tutorial Abstracts of ACL-IJCNLP 2009
Year:
2009

Citing 8
Cited 4

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Abstract

The identification of different nominal phrases in a discourse as used to refer to the same (discourse) entity is essential for achieving robust natural language understanding (NLU). The importance of this task is directly amplified by the field of Natural Language Processing (NLP) currently moving towards high-level linguistic tasks requiring NLU capabilities such as e.g. recognizing textual entailment. This tutorial aims at providing the NLP community with a gentle introduction to the task of coreference resolution from both a theoretical and an application-oriented perspective. Its main purposes are: (1) to introduce a general audience of NLP researchers to the core ideas underlying state-of-the-art computational models of coreference; (2) to provide that same audience with an overview of NLP applications which can benefit from coreference information.