{
  "id": 6682527,
  "title": "Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)",
  "url": "https://urgent.news/2026/09/10/enabling-knowledge-graph-understanding-at-scale-with-the-explore-your",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T14:03:32.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11569v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale. We address two questions in sequence. First, how effectively can LLMs perform text-to-SPARQL generation given only automatically derived structured metadata and small graph samples, rather than task-specific fine-tuning? We integrate VoID…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}