The OLAC Movie & Video Credit Annotation Experiment seeks to draw connections between names and their associated roles within moving image MARC records using Named Entity Recognition in natural language processing in order to drive more effective discovery interfaces, formulated for sharing as linked data in a manner similar to the Internet Movie Database. This research-based capstone project sought to better understand moving image roles as they relate to relationship designators in the RDA Toolkit, linking them as appropriate, proposing new designators to accommodate the diverse range of roles in the moving image industry, and identifying areas where designator mapping was problematic or not possible. The results found 64 percent of roles could be mapped, 19 percent could be assigned to proposed designators, and 16 percent remained undefined. This research has contributed toward a better understanding of issues related to formulation, inclusion, location, and consistency within moving image MARC records.