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A Bayesian interpretation of cross‐linguistic ambiguity tests
Author(s) -
Langston Christopher
Publication year - 2023
Publication title -
mind and language
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.905
H-Index - 68
eISSN - 1468-0017
pISSN - 0268-1064
DOI - 10.1111/mila.12423
Subject(s) - ambiguity , linguistics , interpretation (philosophy) , contrast (vision) , psychology , bayesian probability , artificial intelligence , computer science , philosophy
Cross‐linguistic comparisons serve as empirical tests generating evidence for and against lexical ambiguity in words like “good”, “know”, “the”, “can”, and “may”. Critics question such comparisons' validity. This article examines how cross‐linguistic comparisons are treated as tests and shows that they have two predominant forms: one modeled on modus tollens, and another on Bayes' theorem, where the former is an enthymematic version of the latter. This analysis reveals the strengths and weaknesses of cross‐linguistic comparisons, and thereby guides interpretation of their results. It concludes that cross‐linguistic comparisons generally yield stronger evidence against lexical ambiguity than for it.