Optimality Theory (OT) (Prince & Smolensky, 1993) characterizes linguistic knowledge as a ranked set of constraints that select the best possible output form of a word given a particular input. OT assumes that constraints are ordered transitively with respect to their violability. An artificial language learning paradigm was used to test this assumption by teaching participants to pronounce words that provided evidence about three constraints affecting the stress patterns of words. The words demonstrated that the first constraint outranked the second and the second outranked the third. The relationship between the first and third could only be derived from the transitive nature of the system. Three experiments tested whether speakers could determine the stress patterns of words requiring knowledge of the relationship between these two constraints. Evidence was found for a transitively ordered constraint system as well as a system that stores commonly heard stress patterns as metrical templates.