Coreference resolution with loose transitivity constraints

Authors:
Xinxin Li;Xuan Wang;Shuhan Qi
Affiliations:
Shenzhen Graduate School, Harbin Institute of Technology, ShenZhen, China;Shenzhen Graduate School, Harbin Institute of Technology, ShenZhen, China;Shenzhen Graduate School, Harbin Institute of Technology, ShenZhen, China
Venue:
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Year:
2011

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Abstract

Our system treats coreference resolution as an integer linear programming (ILP) problem. Extending Denis and Baldridge (2007) and Finkel and Manning (2008)'s work, we exploit loose transitivity constraints on coreference pairs. Instead of enforcing transitivity closure constraints, which brings O(n3) complexity, we employ a strategy to reduce the number of constraints without large performance decrease, i.e., eliminating coreference pairs with probability below a threshold θ. Experimental results show that it achieves a better performance than pairwise classifiers.