Gaussian Mixture Latent Vector Grammars
Table 3: Parsing accuracy on the testing data of WSJ. EX indicates the exact match score.
['Model', 'dev (all) F1', 'test≤40 F1', 'test≤40 EX', 'test (all) F1', 'test (all) EX']
It can be seen that GM-LVeG-S produces the best F1 scores on both the development data and the testing data. It surpasses the Berkeley parser by 0.92% in F1 score on the testing data. Its exact match score on the testing data is only slightly lower than that of LVG-D-16.