Using inconsistency detection to overcome structural ambiguity

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18 Scopus citations


The Inconsistency Detection Learner (IDL) is an algorithm for language 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 reference to other overt data of the language. The IDL does this by attempting 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 computational results from an implementation of the IDL using an optimalitytheoretic system of metrical stress grammars.

Original languageEnglish (US)
Pages (from-to)219-253
Number of pages35
JournalLinguistic Inquiry
Issue number2
StatePublished - Mar 2004

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language


  • Language acquisition
  • Learnability
  • Metrical phonology
  • Optimality theory


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