Using a Bayesian Framework to Identify the Referent of Definite Descriptions

Sehyeong Cho and Anthony Maida

This paper describes a principled method for weighing evidence from various sources in order to identify the referent of a description that is not guaranteed to be correct. We adopt assumptions consistent with Gricean maxims of conversation, thereby mapping the problem into a simple Bayesian framework that allows us model the behavior of the speaker. This framework has been shown to give us the advantage of being able to systematically incorporate evidence from various knowledge that a listener may acquire during conversation. In particular, knowledge about speaker’s beliefs and knowledge about focus are shown to be easily incorporated. Guidelines for handling other kinds of evidence are also


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