Intensionalizing Abstract Meaning Representations: Non-Veridicality and Scope

TL;DR

This paper enhances Abstract Meaning Representation (AMR) by integrating non-veridicality and scope handling through a novel mapping to Simply-Typed Lambda Calculus, inspired by linguistic semantics, enabling better representation of intensional contexts.

Contribution

It introduces a new approach to represent non-veridicality in AMR using a mapping to STLC and a scope node, improving the handling of intensional contexts and scope ambiguities.

Findings

Successfully models non-veridical contexts without layered graphs.

Provides explicit semantics for de re/de dicto ambiguities.

Enables derivation of intermediate scope readings.

Abstract

Abstract Meaning Representation (AMR) is a graphical meaning representation language designed to represent propositional information about argument structure. However, at present it is unable to satisfyingly represent non-veridical intensional contexts, often licensing inappropriate inferences. In this paper, we show how to resolve the problem of non-veridicality without appealing to layered graphs through a mapping from AMRs into Simply-Typed Lambda Calculus (STLC). At least for some cases, this requires the introduction of a new role :content which functions as an intensional operator. The translation proposed is inspired by the formal linguistics literature on the event semantics of attitude reports. Next, we address the interaction of quantifier scope and intensional operators in so-called de re/de dicto ambiguities. We adopt a scope node from the literature and provide an explicit multidimensional semantics utilizing Cooper storage which allows us to derive the de re and de dicto scope readings as well as intermediate scope readings which prove difficult for accounts without a scope node.