In comparison with our tree kernel-based method, it shows that 1) when using golden anaphoric zero anaphors, the feature-based method performs about 11%, 17% and 15 lower in precision, recall and F-measure, respectively; 2) when golden zero anaphors are given and feature-based anaphoricity determination is applied, the featurebased method performs about 5%, 18% and 17 lower in precision, recall and F-measure, respectively; and 3) when tree kernel-based zero anaphor detection and feature-based anaphoricity determination are applied, the feature-based method per-forms about 7%, 8% and 10 lower in precision, recall and F-measure, respectively.
given a zero anaphor candidate, it is critical to construct a proper parse tree structure for tree kernel-based zero anaphor detection.