Abstract: A robot participating in natural dialogue with a human interlocutor may need to discuss, reason about, or initiate actions concerning dialogue-referenced entities. To do so, the robot must first identify or create new representations for those entities, a capability known as reference resolution. We previously presented algorithms for resolving references occurring in definite noun phrases. In this paper we present GH-POWER: an algorithm for resolving references occurring in a wider array of linguistic forms, by making novel extensions to the Givenness Hierarchy, and evaluate GH-POWER on natural task-based human-human and human-robot dialogues.
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