1999 NounPhraseCoreferenceAsClustering

(Wagstaff & Cardie, 1999) ⇒ Kiri Wagstaff, Claire Cardie. (1999). “Noun Phrase Coreference as Clustering.” In: Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP 1999).

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

Notes

It proposes an Unsupervised Learning Algorithm to the Entity Mention Coreference Resolution Task (Noun Phrase Coreference Resolution).
It requires Noun Phrase Detection (but no Full Syntactic Parse).
It focuses on Base Noun Phrases (not Complex Noun Phrases).
It handles several types of Noun Phrase Coreference Resolution, not just Pronoun Resolution.
It does not learn the weights associated with each term in the distance metric.

Cited By

~171 http://scholar.google.com/scholar?q=%22Noun+Phrase+Coreference+as+Clustering.%22+1999

Quotes

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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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1999 NounPhraseCoreferenceAsClustering	Kiri Wagstaff			Noun Phrase Coreference as Clustering			http://acl.ldc.upenn.edu/W/W99/W99-0611.pdf