A knowledge-driven approach to text meaning processing

Our goal is to be able to answer questions about text that go beyond facts explicitly stated in the text, a task which inherently requires extract-ing a “deep ” level of meaning from that text. Our approach treats meaning processing fun-damentally as a modeling activity, in which a knowledge base of common-sense expectations guides interpretation of text, and text suggests which parts of the knowledge base might be relevant. In this paper, we describe our ongo-ing investigations to develop this approach into a usable method for meaning processing.