On the foundations of relaxation labeling processes
Readings in computer vision: issues, problems, principles, and paradigms
C4.5: programs for machine learning
C4.5: programs for machine learning
WordNet: a lexical database for English
Communications of the ACM
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
SemEval-2010 task 1: Coreference resolution in multiple languages
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
SemEval-2010 task 1: Coreference resolution in multiple languages
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
RelaxCor participation in CoNLL shared task on coreference resolution
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Rule and tree ensembles for unrestricted coreference resolution
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Poly-co: a multilayer perceptron approach for coreference detection
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Coreference resolution: an empirical study based on SemEval-2010 shared Task 1
Language Resources and Evaluation
A constraint-based hypergraph partitioning approach to coreference resolution
Computational Linguistics
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This paper describes the participation of RelaxCor in the Semeval-2010 task number 1: "Coreference Resolution in Multiple Languages". RelaxCor is a constraint-based graph partitioning approach to coreference resolution solved by relaxation labeling. The approach combines the strengths of groupwise classifiers and chain formation methods in one global method.