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ACL
2009

Capturing Salience with a Trainable Cache Model for Zero-anaphora Resolution

10 years 9 months ago
Capturing Salience with a Trainable Cache Model for Zero-anaphora Resolution
This paper explores how to apply the notion of caching introduced by Walker (1996) to the task of zero-anaphora resolution. We propose a machine learning-based implementation of a cache model to reduce the computational cost of identifying an antecedent. Our empirical evaluation with Japanese newspaper articles shows that the number of candidate antecedents for each zero-pronoun can be dramatically reduced while preserving the accuracy of resolving it.
Ryu Iida, Kentaro Inui, Yuji Matsumoto
Added 16 Feb 2011
Updated 16 Feb 2011
Type Journal
Year 2009
Where ACL
Authors Ryu Iida, Kentaro Inui, Yuji Matsumoto
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