{
  "id": 18036,
  "url": "https://arxiv.org/abs/2608.09028v1",
  "title": "PolicyKG: An Agentic LLM Pipeline for Translating Institutional Policies into SHACL Knowledge Graphs",
  "summary": "Institutional policies stay in natural language while the systems that check compliance demand machine-readable constraints. Bridging that gap is still done by hand. PolicyKG closes the loop. It is an LLM pipeline that reads a policy PDF, classifies each sentence as an obligation, permission, or prohibition, lifts the label into first-order deontic logic, and emits SHACL constraints. Four stages run on a LangGraph state machine with per-stage validators. The piece that matters most is the Corpus",
  "authors": "Ponkrit Kaewsawee, Chaklam Silpasuwanchai, Chutiporn Anutariya",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-10T02:28:57.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/18036",
  "original_url": "https://arxiv.org/abs/2608.09028v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}