Identifying relevant Persona or Knowledge for conversational systems is a critical component of grounded dialogue response generation. However, each grounding has been studied in isolation with more practical multi-context tasks only recently introduced. We define Persona and Knowledge Dual Context Identification as the task to identify Persona and Knowledge jointly for a given dialogue, which could be of elevated importance in complex multi-context Dialogue settings. We develop a novel grounding retrieval method that utilizes all contexts of dialogue simultaneously while also requiring limited training via zero-shot inference due to compatibility with neural Q \& A retrieval models. We further analyze the hard-negative behavior of combining Persona and Dialogue via our novel null-positive rank test.