Optional Deep Case Filling and Focus Control with Mental Images: ANTLIMA-KOREF

Abstract

The connection of vision and natural language systems in AI research relies on what is often called reference semantics. In the situation of a radio reporter for soccer games an utterance must be perceptually anchored and coherent in order to be understandable to a listener not able to see the scene. Accordingly, the speaker must be able to anticipate the listeners' understanding by means of mental images. In this paper we demonstrate the comparison of mental images and visual perception on the level of spatial relations and show how to employ the results for cooperatively filling optional deep cases and for controlling the use of underspecific definite descriptions. This paper has been accepted for IJCAI-95, Montreal. 1 Introduction The project VITRA has started in 1985 as part of the German special collaboration programme SFB 314, AI & Knowledge-Based Systems. It deals with the relations between speaking and seeing, and aims at a completely operational form of reference semantics ...