The safe navigation of autonomous vehicles (AVs) is dependent on accurate and up-to-date information, typically assuming access to pre-generated, high-definition map data, which limits the utility of AVs in novel environments. To overcome this, traffic signs have been considered as a rich and reliable source of real-time data to aid AV operations, but existing research has focused primarily on the classification of standard traffic signs and sign text recognition. In this research, we explore the problem of parsing the semantics of traffic signs in a manner which is useful for downstream control and navigation systems.