Learning Noun Phrase Anaphoricity to Improve Coreference
Resolution: Issues in Representation and Optimization
Vincent Ng.
42nd Annual Meeting of the Asssociation for Computational Linguistics (ACL), 2004.
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Abstract
Knowledge of the anaphoricity of a noun phrase might be profitably
exploited by a coreference system to bypass the resolution of
non-anaphoric noun phrases.
Perhaps surprisingly,
recent attempts to incorporate automatically acquired
anaphoricity information into coreference systems, however,
have led to the degradation in resolution performance.
This paper examines several key issues in computing
and using anaphoricity information to improve learning-based
coreference systems.
In particular, we present a new corpus-based approach to
anaphoricity determination.
Experiments on three standard coreference data sets
demonstrate the effectiveness of our approach.