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Different link prediction models capture unique knowledge, but combining them reveals a saturation point, leaving many queries unanswered.
The integration of LLMs in ontology engineering reveals that fewer than 20% of extracted triples introduce unseen properties, challenging assumptions about legal data completeness.
Relying solely on Small Language Models, this approach achieved a surprising 27.80% content score while reducing reasoning bias.
