LLM repairs Knowledge Graph (Apple MacBook)
**LLM Knowledge Graph Repair: Promise and Limitations** Current research reveals LLMs excel at structural pattern recognition (90%+ format adherence) but struggle with semantic accuracy, achieving only 20-40% correctness in critical domains like healthcare. While promising for detection and assistance, LLMs require hybrid neurosymbolic approaches with human oversight for reliable knowledge graph repair. Future solutions likely combine neural flexibility with symbolic reasoning validation.