Acquisition and Maintenance of Knowledge Bases for Natural  Language Processing Systems
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This research is joint work of Sergei Nirenburg at Carnegie             Mellon University and Victor Raskin at Purdue University. Their goal            is to advance the state of the art in knowledge bases for natural               language processing.  They are building knowledge bases about words,            word meanings and word relationships, extended beyond "toy" domains             to be comprehensive enough for natural language processing in                   realistic situations.  These kinds of "computational lexicography"              knowledge bases are fundamental to automatic computer systems for               analyzing natural language and for generating natural language                  output.                                                                                 The significance of this research is that automatic                     processing of natural language is a major component in developing               computer systems interface.  Computerized knowledge bases about word            meanings and world knowledge are indispensable to natural language              processing systems.  This work begins to build the framework for                such knowledge bases and the tools for acquiring their content, in a            way which will be useful to many research groups and suitable for               diverse applications.
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