The ability to ground conversational referents is a key requirement for human dialogue. This process, known as reference resolution, has received much attention from both psycholinguists seeking to understand how humans process language and computer scientists seeking to improve the performance of language-capable agents. However, the majority of previous research has focused on what we term closed-world reference resolution, in which the set of possible referents is assumed to be known a priori. In this paper we present a domainindependent model of open-world reference resolution which appropriately handles uncertain knowledge, and the results of an empirical human-subject experiment conducted to verify the model’s predictions.