Entity-based cross-document coreferencing using the Vector Space Model
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Whither written language evaluation?
HLT '94 Proceedings of the workshop on Human Language Technology
Unsupervised relation disambiguation using spectral clustering
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
AUG: a combined classification and clustering approach for web people disambiguation
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
IRST-BP: web people search using name entities
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Shallow semantics for coreference resolution
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Name discrimination by clustering similar contexts
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Dynamic parameters for cross document coreferece
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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The accuracy of a Cross Document Coreference system depends on the amount of context available, which is a parameter that varies greatly from corpora to corpora. This paper presents a statistical model for computing name perplexity classes. For each perplexity class, the prior probability of coreference is estimated. The amount of context required for coreference is controlled by the prior coreference probability. We show that the prior probability coreference is an important factor for maintaining a good balance between precision and recall for cross document coreference systems.