Ground Truth

The correct, verified answer for a given data point, used as the reference against which a model's predictions are measured. In supervised learning, ground truth labels are what the model is trained to reproduce. The term reflects the assumption that this is the definitive reality the model should learn to reflect, though in practice ground truth is only as good as the humans or processes that produced it.
See also: supervised learning, data labeling / annotation, Evaluation.