The Structure-Richness Tradeoff

AI-generated ontologies score higher on structural metrics, more standardized vocabulary, more controlled terminology, higher consistency scores. Human-generated ontologies score higher on semantic richness, more instances captured, better hierarchical alignment, more nuanced relationships.

The pattern: AI produces cleaner, smaller structures. Humans produce messier, richer ones.

This tradeoff appears fundamental to current LLM capabilities. The models optimize for consistency and pattern adherence, which produces structural regularity but loses domain nuance. Humans introduce variation that reduces structural metrics but captures more of what actually matters.

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