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- Ground truth is the verified, correct answer or label for each example, representing reality as accurately as possible. Models learn from and are evaluated against ground truth, so validating its quality during Data Understanding is critical. Poor or biased ground truth produces a poor model regardless of algorithm quality, which is why CPMAI emphasizes validating it.