Research on Semantic Role Information in Anaphora Resolution
Guodong Zhou · Zhongwen xinxi xuebao · 2009
This paper proposes a machine learning-based approach to coreference resolution with special focus on the semantic role labeling information of the anaphor and the antecedent candidate.We first combine the baseline system with semantic role features which are acquired from ASSERT system.Furthermore,we analyze the integration of semantic role feature with detailed pronoun type knowledge,which suggests that incorporating semantic role information of anaphor and its antecedent candidates is beneficial to coreference resolution,especially to pronouns.Evaluation on the ACE-2003 NWIRE benchmark corpus shows that systems with proper handling of semantic role information achieves significant improvements of 3.4% in recall and 1.8% in F-measure respectively.