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This paper presents GRID, an end-to-end framework for constructing security knowledge graphs from cyber threat intelligence (CTI) articles using LLMs, introducing a task-bank reward training method to improve precision and recall without expensive LLM-as-judge rewards. The approach achieves strong results on a benchmark of 249 CTI articles from five sources.