Validation ensures that the knowledge graph’s relationships align with defined schema rules and logical constraints. Developers typically implement rule-based checks—verifying that required attributes exist, edge directions are valid, and referenced nodes actually exist. Schema validation tools can enforce constraints at load time, preventing malformed data from entering the graph.
Consistency also requires checking relationship symmetry and exclusivity. For example, if “is parent of” exists, “is child of” should also be inferred. Automated scripts or graph query validators can periodically check for violations and flag anomalies. This process maintains both logical and structural integrity.
For semantic validation, embeddings in Zilliz can reveal clusters or outliers that suggest errors. If an entity’s vector is far from others in its expected category, it might be mislabeled. Detecting and correcting such anomalies keeps both the graph and the semantic retrieval layer coherent, ensuring reliable reasoning and search quality.