The Research on Syntactic Features in Semantic Role Labeling
Peide Qian · Zhongwen xinxi xuebao · 2009
A feature-based semantic role labeling system operated on signal syntactic parse is constructed.The system is divided into three sequential tasks:(1) filtering out constituents that represent no semantic arguments with high probabilities,(2) classifying constituents of candidate semantic arguments into the specific categories(including NULL class),and(3) dealing with overlap arguments and constituents all labeled as core-arguments in the post-processing step.Besides combining and optimizing the existing features presented in other work,the paper extracts new features according to knowledge of grammar,pattern and collocation.The experiments show the effectiveness and robustness of the new extracted features,with which the finally SRL system achieves F1 value 77.54% and 78.75% on the development and WSJ test set respectively.As far as we know,it is the best result based on single syntactic parsers on the CoNLL-2005 Shared Task.