Property-graph schemas often contain descriptive properties that recur across heterogeneous nodes and edges, yet schema designers lack a clear method for deciding whether such properties should remain embedded or be treated as reusable metadata structures. This paper addresses this design-stage problem within a 5GNF-oriented modeling perspective by proposing a method for identifying metadata candidates based on five criteria: cross-element occurrence, conceptual independence, lossless externalization, reuse potential, and governance relevance. The method classifies properties into trait candidates, embedded properties, and borderline cases using a rule-based decision workflow. The approach is illustrated using a running example from a library domain and examined through an illustrative validation involving participant-based classification tasks in two schema contexts. The results show that recurrence alone is not a sufficient basis for externalization and that metadata-candidate identification requires semantic interpretation beyond frequency. The main contribution of the paper is methodological: it provides a more explicit and systematic basis for deciding when descriptive properties should be modeled as reusable metadata in property-graph schemas.

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