Semantic Role Labeling for Learner Chinese: the Importance of Syntactic Parsing and L2-L1 Parallel Data
Table 8: Accuracies of different neural-parser-based models on the two test data sets.
['L2', 'Baseline', 'P 78.26', 'R 63.38', 'F 70.04']
Different from the PCFGLA model, the SRL-consistent trees only yield a slight improvement on the L2 data. On the contrary, retraining the SRL classifier is much more effective. This experiment highlights the different strengths of different frameworks for parsing. Though for standard in-domain test, the neural parser performs better and thus is more and more popular, for some other scenarios, the PCFGLA model is stronger.