Acquiring and Representing Background Knowledge for a Natural Language Processing System

Andrei Mikheev and Marc Moens

In this paper we describe a methodology for acquiring, structuring and encoding background knowledge for natural language processing. The methodology has been used for the development of a knowledge base for a system which processes patient discharge summaries in a restricted medical domain. On the basis of some example texts and system output, we will illustrate how acquired and represented background knowledge is used in processing to yield the desired interpretations.

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