This paper discusses how Information Extraction is used to understand and manage Dialogue in the EU-funded Companions project. This will be discussed with respect to the Senior Companion, one of two applications under development in the EU-funded Companions project. Over the last few years, research in human-computer dialogue systems has increased and much attention has focused on applying learning methods to improving a key part of any dialogue system, namely the dialogue manager. Since the dialogue manager in all dialogue systems relies heavily on the quality of the semantic interpretation of the user’s utterance, our research in the Companions project, focuses on how to improve the semantic interpretation and combine it with knowledge from the Knowledge Base to increase the performance of the Dialogue Manager. Traditionally the semantic interpretation of a user utterance is handled by a natural language understanding module which embodies a variety of natural language processing techniques, from sentence splitting, to full parsing. In this paper we discuss the use of a variety of NLU processes and in particular Information Extraction as a key part of the NLU module in order to improve performance of the dialogue manager and hence the overall dialogue system.