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Analogy in GrammarForm and Acquisition$
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James P. Blevins and Juliette Blevins

Print publication date: 2009

Print ISBN-13: 9780199547548

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780199547548.001.0001

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Modeling analogy as probabilistic grammar *

Modeling analogy as probabilistic grammar *

(p.185) 9 Modeling analogy as probabilistic grammar*
Analogy in Grammar

Adam Albright

Oxford University Press

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

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