Abstract: Argument identification plays an important role for argument classification task in semantic role labeling.According to the headwords of the constituents，this paper researches on argument identification algorithm.The experiment shows that 98.78% of arguments on train set and 97.17% on test set are identified.At the same time，most of NULL arguments are pruned.The existed features are re-combined and optimized to capture more useful information.A SVM classifier is used in the semantic role labeling system，which took syntactic constituents as labeled units.The F1-score of SRL on test set achieves 77.84%.So far as it is known，it is one of the best result based on single syntactic parser in literatures.