SOURCE-LINKED INTELLIGENCE
Do General NLP Embeddings Capture Ontological Reasoning?
General-purpose NLP embedding models perform well on linguistic tasks, but their ability to capture symbolic ontological structure remains unclear. We introduce AVA, a systematic framework for evaluating whether embeddings distinguish logic-sensitive relational semantics in ontologies and knowledge graphs. AVA comprises 171,007 contrastive triplets derived from 163 heterogeneous ontologies using hierarchy inversion, relation substitution, and disjointness injection. Each triplet contains an ontology statement, a semantically equivalent paraphrase, and a logic-sensitive hard negative with contr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T18:03:23.000Z
First collected: 2026-09-21T06:41:57.136Z. This is not the publication date.