Greedy Transition-Based Dependency Parsing withDiscrete and Continuous Supertag Features
Table 1: Accuracy of different parsing models built on the two top words of the stack (UAS, LAS); development set.
['[BOLD] Features', '[BOLD] UAS', '[BOLD] LAS']
We see that supertag features (SUPERTAG, SD) are vastly superior to POS tags (POS) as well as word forms (FORM), and we see that the continuous features in the SD model (with k=320) do slightly better than the boolean features in the SUPERTAG model when it comes to labeled attachment score.