Ground Truth

In machine learning and LLM evaluation, the label or output generally accepted as the correct answer for a given input. In LLM application engineering, ground truth sources extend to human review, customer confirmation, and downstream system feedback, often with time delays, giving rise to delayed ground truth as a distinct engineering problem.