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Static and dynamic vector semantics for lambda calculus models of natural language

Sadrzadeh M., Muskens R.

Journal of Language Modelling

2018

Vol. 6, No. 2

319--351

Vector models of language are based on contextual aspects of language – distributions of words and how they co-occur in text. Truth conditional models focus on logical aspects of language and on how words combine to contribute to these aspects. In the truth conditional approach, there is a focus on the denotations of phrases. In vector models, the degree of co-occurrence of words in context determines how similar their meanings are. The two approaches have complementary virtues. In this paper we combine them and develop a vector semantics for language, based on the typed lambda calculus. We provide two types of vector semantics: a static one using techniques from the truth conditional tradition, and a dynamic one with a form of interpretation inspired by Heim’s context change potentials. We show, with examples, how the dynamic model can be applied to entailment between a corpus and a sentence.