Principle Based Semantics for HPSG

TL;DR

This paper introduces a constraint-based semantic formalism for HPSG that efficiently handles ambiguities in German syntax, enabling incremental interpretation and direct inference without generating multiple interpretations.

Contribution

It proposes a novel formalism using underspecified discourse representations that integrate syntax and semantics for HPSG, improving ambiguity resolution and inference.

Findings

UDRS allow monotonic incremental interpretation

Semantic representations include truth conditions and proof theory

Efficient handling of quantifier scope and distributivity ambiguities

Abstract

The paper presents a constraint based semantic formalism for HPSG. The advantages of the formlism are shown with respect to a grammar for a fragment of German that deals with (i) quantifier scope ambiguities triggered by scrambling and/or movement and (ii) ambiguities that arise from the collective/distributive distinction of plural NPs. The syntax-semantics interface directly implements syntactic conditions on quantifier scoping and distributivity. The construction of semantic representations is guided by general principles governing the interaction between syntax and semantics. Each of these principles acts as a constraint to narrow down the set of possible interpretations of a sentence. Meanings of ambiguous sentences are represented by single partial representations (so-called U(nderspecified) D(iscourse) R(epresentation) S(tructure)s) to which further constraints can be added monotonically to gain more information about the content of a sentence. There is no need to build up a large number of alternative representations of the sentence which are then filtered by subsequent discourse and world knowledge. The advantage of UDRSs is not only that they allow for monotonic incremental interpretation but also that they are equipped with truth conditions and a proof theory that allows for inferences to be drawn directly on structures where quantifier scope is not resolved.