Reference: P. Clark, L. Duncan, H. Holmback, T. Jenkins, J. Thompson. In: Proceedings of Human Language Technologies Conference (HLT'02), pages 87-93, Ed: M. Marcus, CA:Kaufmann, 2002. 2002.
Abstract: As part of a longer-term goal to construct an aerospace knowledge-base (KB), we are developing techniques for interpreting text about aircraft systems and then adding those interpretations to the KB. A major challenge in this task is that much of what is written builds on unstated, shared, general knowledge about aircraft, and such prior knowledge is needed to fully understand the text. To address this challenge, we are using a more general KB about aircraft to create strong, prior expectations about what might be stated in that text, then treating the language understanding task as one of incrementally extending and refining that prior knowledge. The KB constrains the possible interpretations of the text, allowing it to be placed in the appropriate context and helping identify when statements can be taken literally or need to be coerced or modified to be understood correctly. In this paper we present this approach and discuss its underlying assumptions and range of applicability. The significance of this work is twofold: It illustrates the critical role background knowledge plays in fully understanding language, and it provides a simple model for how that understanding can take place, based on the iterative refinement of a representation using information extracted from text.
Slide Presentation (PowerPoint): http://www.cs.utexas.edu/users/pclark/papers/hlt.ppt