Knowledge graphs have emerged as a widely used method for representing and organizing information in a structured, graph-based form that facilitates understanding, navigation, and utilization by both machines and humans. The graphs model classes, entities and their relationships as nodes and edges in a graph. Natural logics are logics where sentences are expressed in a stylized form of natural language and where computational reasoning is conducted directly on the natural logic phrases, rather than on the underlying formal logic. NaturaLog is a dialect of natural logics that comes with a graph form, enabling knowledge in the knowledge base to be visualized and processed as graphs. NaturaLog thus offers an approach to natural logic graphs and additionally incorporates logical quantifiers, compound terms, and deductive reasoning, thereby going beyond the capabilities of traditional knowledge graph models. Here we specifically discuss the affinity between knowledge graphs and the natural logic graphs of NaturaLog.