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http://purl.org/dc/terms/description <span><p><em><strong>Early Lessons from a Work in Progress</strong></em></p><p><strong>The Challenge</strong></p><ul><li>Knowledge graphs represent what is true, but in domains like music and content classification, truth is contested, evolving, and subjective.</li><li>When systems flatten ambiguity, they lose organizational intelligence.</li><li>With AI agents now consuming the graphs, the problem is urgent.</li><li>Agents can't distinguish institutionally-ratified claims from contested ones, producing not hallucination but false consensus.</li><li>Emerging standards like OKF standardize a grain for structural metadata, but provide no vocabulary for epistemic metadata or typed relation: confidence, verification status, decision provenance, temporal validity.</li></ul><p><strong>A Solution</strong></p><p>We propose a working augmentation: an approach that borrows both from OKF and RDF, but with separable conventions for the dimensions that emerge through collaboration at scale.</p><p><strong>What we did</strong></p><ul><li>What we built.</li><li>The ambiguous situations that shaped each decision.</li></ul><p><strong>What we learned</strong> — including why inconsistency between sources is often signal, not noise.</p></span> https://w3id.org/np/RAponOzx1XgfGZ0ElERkQxS9ReVJ0L8IBid1q_Agr7O3Y/ai-and-the-evolving-subjective http://purl.org/dc/terms/isPartOf https://w3id.org/spaces/semantic-data-ny/2026 https://w3id.org/np/RAponOzx1XgfGZ0ElERkQxS9ReVJ0L8IBid1q_Agr7O3Y/ai-and-the-evolving-subjective http://purl.org/pav/authoredBy https://w3id.org/np/RAponOzx1XgfGZ0ElERkQxS9ReVJ0L8IBid1q_Agr7O3Y/mark-grey https://w3id.org/np/RAponOzx1XgfGZ0ElERkQxS9ReVJ0L8IBid1q_Agr7O3Y/ai-and-the-evolving-subjective http://purl.org/pav/authoredBy https://w3id.org/np/RAponOzx1XgfGZ0ElERkQxS9ReVJ0L8IBid1q_Agr7O3Y/nicole-buckenwolf https://w3id.org/np/RAponOzx1XgfGZ0ElERkQxS9ReVJ0L8IBid1q_Agr7O3Y/ai-and-the-evolving-subjective 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