Effective Inference for Generative Neural Parsing
Table 4: Results when the best setting from Section 6 is rerun with Open action pruning with context size c=2 and various pruning fractions p. Lower values of p indicate more aggressive pruning, while p=1 means no pruning is performed.
['[ITALIC] p', '6/26', '7/26', '8/26', '9/26', '10/26', '11/26', '1']
We observe that performance is on par with the unpruned setup (at most 0.1 absolute difference in F1 score) for p as low as 8/26≈0.308. Setting p to 7/26≈0.269 results in a drop of 0.18, and setting p to 6/26≈0.231 results in a drop of 0.40. Hence, degradation begins to occur right around the empirically-motivated threshold of 6/26 given above, but we can prune 1−8/26≈69.2% of Open successors with minimal changes in performance.