Paper: A Global Relaxation Labeling Approach to Coreference Resolution

ACL ID C10-2125
Title A Global Relaxation Labeling Approach to Coreference Resolution
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

This paper presents a constraint-based graph partitioning approach to corefer- ence resolution solved by relaxation label- ing. The approach combines the strengths of groupwise classifiers and chain forma- tion methods in one global method. Ex- periments show that our approach signifi- cantly outperforms systems based on sep- arate classification and chain formation steps, and that it achieves the best results in the state of the art for the same dataset and metrics.