Classical unification is strict in the sense that it requires a perfect agreement between the terms being unified. In practise, data are seldom error-free and can contain incorrect information. Classical unification fails when the data are imperfect. Relaxed unification is a new formalism that relaxes the rigid constraints of classical unification and enables reasoning under uncertainty and in the presence of inconsistent data. We propose a probabilistic evaluation function to evaluate the degree of mismatches in relaxed terms and illustrate its use with an example.