Chapter

Modeling analogy as probabilistic grammar*

Adam Albright

in Analogy in Grammar

Published in print July 2009 | ISBN: 9780199547548
Published online September 2009 | e-ISBN: 9780191720628 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780199547548.003.0009
Modeling analogy as probabilistic grammar*

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Models of analogy must be non-deterministic enough to handle gradient data, but must also explain why analogy obeys some striking restrictions: only a tiny subset of logically possible analogies are actually attested. This chapter discusses several unattested types of analogy, and considers their implications for formal models. Gradience and notable restrictions are best modeled using a grammar of probabilistic rules.

Keywords: analogy; type frequency; base of analogy; probabilistic rules; exemplar models; computational modeling; Spanish diphthongization

Chapter.  11045 words.  Illustrated.

Subjects: Psycholinguistics

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