Current eXplainable AI (XAI) methods tend to provide only one-way explanations, limiting user interaction and contextual adaptation. Social Explainable AI (sXAI) addresses this by enabling interactive, co-constructed explanations. This paper demonstrates how Contextual Importance and Utility (CIU) and Knowledge Graphs (KGs) can generate structured and context-aware explanations. We present a proof-of-concept implementation that shows how KGs facilitate dynamic dialogues, making sXAI practical. Our findings highlight the potential of CIU and KGs in creating more user-centered, interactive explainability frameworks.