A new extension to the PROV-O ontology, called PROV-CRED, has been developed to address the issue of varying accuracy in knowledge graph facts. This extension allows for the reliability, AI model performance, and accreditation of data triples to be queried. The goal is to prevent compounding errors in AI reasoning by making data provenance more transparent and evaluable. This work was presented by Mary Ann Tan at the SEMANTICS 2026 conference. AI
IMPACT Enhances AI reasoning by improving the reliability and queryability of knowledge graph data.
RANK_REASON The item describes a new extension to an ontology for knowledge graphs, presented at a conference, which is a research-oriented development. [lever_c_demoted from research: ic=1 ai=1.0]
Read on Mastodon — mastodon.social →
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →