Integrating Natural Language Processing and Knowledge Based Processing

Rebecca Passonneau, Carl Weir, Tim Finin, Martha Palmer

A central problem in text-understanding research is the indeterminacy of natural language. Two related issues that arise in confronting this problem are the need to make complex interactions possible among the system components that search for cues, and the need to control the amount of reasoning that is done once cues have been discovered. We identify a key difficulty in enabling true interaction among system components and we propose an architectural framework that minimizes this difficulty. A concrete example of a reasoning task encountered iu an actual text-understanding application is used to motivate the design principles of our framework.

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