From Learning Resources to Competencies: LLM-Based Tagging with Evidence and Graph Constraints
Researchers developed an LLM-based pipeline that automatically tags learning resources with competencies from structured frameworks, combining language models with graph constraints and evidence extraction. The system achieved strong performance metrics (0.57 micro-F1, 0.82 MRR) while providing transparent, auditable evidence spans—outperforming traditional baselines and addressing the labor-intensive challenge of manual resource tagging in educational systems.