DisCoCat for Donkey Sentences
Lachlan McPheat (University College London), Daphne Wang (University, College London)
TL;DR
This paper extends the DisCoCat framework to parse and model Geach's donkey sentences using a type-logical syntax, integrating relational and vector space semantics for compositional meaning.
Contribution
It introduces a novel type-logical syntax for donkey sentences within the DisCoCat framework, combining relational and vector space semantics.
Findings
Successful parsing of donkey sentences using the new syntax
Integration of relational and vector space semantics
Extension of DisCoCat to discourse and determiners
Abstract
We demonstrate how to parse Geach's Donkey sentences in a compositional distributional model of meaning. We build on previous work on the DisCoCat (Distributional Compositional Categorical) framework, including extensions that model discourse, determiners, and relative pronouns. We present a type-logical syntax for parsing donkey sentences, for which we define both relational and vector space semantics.
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