Automated Standardization of Legacy Biomedical Metadata Using an Ontology-Constrained LLM Agent

arXiv:2604.08552 · cs.DB, cs.AI · Submitted 2026-03-10 · Read on arXiv

cs.DB, cs.AI

Submitted: 2026-03-10

Updated: 2026-09-02

Code: https://github.com/musen-lab/metadata-standardization-agent

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ontology — 86× in this paper · explained in 2 episodes
• Accuracy — 51× in this paper · explained in 1 episode
• Agentic Real-Time Metadata Standardization — 2× in this paper
• Hallucination — 2× in this paper · explained in 3 episodes
• Model Context Protocol — 2× in this paper
• Center for Expanded Data Annotation and Retrieval — 1× in this paper
• Grounding — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Model Context Protocol (MCP) — 1× in this paper · explained in 8 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

Related papers

• Vibe Coding on Trial: Operating Characteristics of Unanimous LLM Juries
• Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering
• Bridging Business Intent and Data: A Benchmark for Automatic Relational Data Product Generation
• DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation
• MaDI-Bench: An End-to-End Data Integration Benchmark
• Eigenius: A Typed Knowledge-Graph DBMS with Epistemic Stratification and Institution-Mediated Reasoning