Data-Driven Grammar Derivation is a grammar induction methodology that systematically constructs formal grammatical rules from empirical linguistic data through automated pattern recognition and statistical inference, distinguishing itself from rule-based or manually encoded approaches by its reliance on observable usage instances as the primary source of grammatical generalization.