This paper describes a method of accurately projecting Propbank roles onto constituents in the CCGbank with near perfect accuracy and automatically annotating verbal categories with the semantic roles of their arguments. The current version of the CCGbank annotates arguments and adjuncts in a suboptimal way – it relies heavily on the Penn Treebank CLR tag, which is widely considered unreliable. By incorporating Propbank roles we are able to modify the derivation to better reflect linguistic reality. Tagging of nodes in the CCG derivation also permits us to annotate verbal categories with semantic roles corresponding to their syntactic arguments, which has strong implications for many NLP tasks.