Probabilistic compositional semantics, purely
Julian Grove, Jean-Philippe Bernardy
July 2023
 

We provide a general framework for the integration of formal semantics with probabilistic reasoning. This framework is conservative, in the sense that it relies only on typed λ-calculus and is thus compatible with logical systems already in use. The framework is also presented modularly, in that it regards probabilistic effects (i.e., sampling and marginalization) as /side effects/, using continuations. We show how our framework may be used to build probabilistic programs compositionally within typed λ-calculus and then illustrate its use on two applications: semantic learning and pragmatic inference within the Rational Speech Act framework.
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Reference: lingbuzz/006284
(please use that when you cite this article)
Published in: In proceedings of JSAI-isAI 2021/LENLS18
keywords: bayesian semantics, probabilities, compositional semantics, monads, continuations, rational speech act, semantics
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