A Situated Context Model for Resolution and Generation of Referring Expressions

Hendrik Zender, Geert-Jan Kruijff, Ivana Kruijff-Korbayová

In: Proceedings of the 12th European Workshop on Natural Language Generation. European Workshop on Natural Language Generation (ENLG-2009) befindet sich EACL 2009 March 30-31 Athens Greece Seiten 126-129 3/2009.


The background for this paper is the aim to build robotic assistants that can naturally interact with humans. One prerequisite for this is that the robot can correctly identify objects or places a user refers to, and produce comprehensible references itself. As robots typically act in environments that are larger than what is immediately perceivable, the problem arises how to identify the appropriate context, against which to resolve or produce a referring expression (RE). Existing algorithms for generating REs generally by-pass this problem by assuming a given context. In this paper, we explicitly address this problem, proposing a method for context determination in large-scale space. We show how it can be applied both for resolving and producing REs.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence