Deep Multitask Learning for Semantic Dependency Parsing
Table 6: Unlabeled (UF) and labeled (LF) parsing performance of freda1 and freda3 on the development set of SemEval 2015 Task 18.
['[EMPTY]', '[BOLD] DM U [ITALIC] F', '[BOLD] DM L [ITALIC] F', '[BOLD] PAS U [ITALIC] F', '[BOLD] PAS L [ITALIC] F', '[BOLD] PSD U [ITALIC] F', '[BOLD] PSD L [ITALIC] F']
We can compare freda3 to freda1 to isolate the effect of modeling higher-order structures. We can see that freda3’s unlabeled performance improves on DM and PAS, but degrades on PSD. This supports our hypothesis, and suggests that in future work, a more careful selection of structures to model might lead to further improvements.