Paper: Noun Phrase Coreference As Clustering

ACL ID W99-0611
Title Noun Phrase Coreference As Clustering
Venue 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
Session Main Conference
Year 1999

This paper introduces a new, unsupervised algo- rithm for noun phrase coreference resolution. It dif- fers from existing methods in that it views corer- erence resolution as a clustering task. In an eval- uation on the MUC-6 coreference resolution cor- pus, 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 im- portantly, the clustering approach outperforms the only MUC-6 system to treat coreference resolution as a learning problem. The clustering algorithm ap- pears to provide a flexible mechanism for coordi- nating the application of context-independent and context-dependent constraints and preferences for accurate partitioning of noun phrases into corefer- ence equivalence classes.