In this paper, we find that the use of deep linguistic representations to predict these semantic labels are more effective than the generally more surface-syntax representations previously employed (Gildea and Palmer (2002)).
we show that the syntactic dependency structure that results load arg0 John arg2 hay arg1 truck Figure 1: PropBank-style semantic representation for both John loaded the truck with hay and John loaded hay into the truck from the extraction of a Tree Adjoining Grammar (TAG) from the PTB, and the features that accompany this structure, form a better basis for determining semantic role labels.