Using inconsistency detection to overcome structural ambiguity. Linguistic Inquiry 35

The Inconsistency Detection Learner (IDL) is an algorithm for lan-guage learning that addresses the problem of structural ambiguity. If an overt form is structurally ambiguous, the learner must be capable of inferring which interpretation of the overt form is correct by refer-ence to other overt data of the language. The IDL does this by attempt-ing to construct grammars for combinations of interpretations of the overt forms, and discarding those combinations that are inconsistent. The potential of this algorithm for overcoming the combinatorial growth in combinations of interpretations is supported by computa-tional results from an implementation of the IDL using an optimality-theoretic system of metrical stress grammars