How to marry a star: probabilistic constraints for meaning in context

TL;DR

This paper presents a probabilistic framework for understanding word meaning in context, modeling lexical shifts and ambiguities through a situation description system that captures how utterances are interpreted mentally.

Contribution

It introduces a novel probabilistic model for context-dependent word meaning, integrating local and global constraints to handle lexical ambiguity and shifts.

Findings

Model effectively captures contextual lexical shifts.

Application to examples demonstrates practical implementation.

Framework accounts for diverse contextualisation phenomena.

Abstract

In this paper, we derive a notion of 'word meaning in context' that characterizes meaning as both intensional and conceptual. We introduce a framework for specifying local as well as global constraints on word meaning in context, together with their interactions, thus modelling the wide range of lexical shifts and ambiguities observed in utterance interpretation. We represent sentence meaning as a 'situation description system', a probabilistic model which takes utterance understanding to be the mental process of describing to oneself one or more situations that would account for an observed utterance. We show how the system can be implemented in practice, and apply it to examples containing various contextualisation phenomena.