You can definitely come up with an hybrid approach. You first get the top k chunks using embeddings and a nearest neighbours algorithm, then you retrieve the relationships from you knowledge graph and you finally merge that in the context that you use to craft the response. I don't know if that will be necessarily be more effective than each approach individually but worth a try if you want to play with these algorithms.