1999 NounPhraseCoreferenceAsClustering

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Subject Headings: Entity Mention Coreference Resolution Algorithm, Clustering Algorithm.

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Abstract

This paper introduces a new, unsupervised algorithm for noun phrase coreference resolution. It differs from existing methods in that it views coreference resolution as a clustering task. In an evaluation on the MUC-6 coreference resolution corpus, the algorithm achieves an F-measure of 53.6%, placing it firmly between the worst (40%) and best (65%) systems in the MUC-6 evaluation. More importantly, the clustering approach outperforms the only MUC-6 system to treat coreference resolution as a learning problem. The clustering algorithm appears to provide a flexible mechanism for coordinating the application of context-independent and context-dependent constraints and preferences for accurate partitioning of noun phrases into coreference equivalence classes.


References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
1999 NounPhraseCoreferenceAsClusteringKiri Wagstaff
Claire Cardie
Noun Phrase Coreference as ClusteringProceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Very Large Corporahttp://acl.ldc.upenn.edu/W/W99/W99-0611.pdf1999