Automating mining of procedural information from surgical texts is an enabling technology for future autonomous surgical robots. This paper examines the question of how to address verb-specific high-level parameters that are not explicitly represented in the text, and where to look for the missing information. Four types of non-local information ought to be considered: lexical, case-based, anatomical and physical modeling considerations. Sample results of the analysis are shown for the verb "mobilize".