The University of Michigan's natural language processing system, called LINK, is a unificationbased system which we have developed over the last four years . Prior to MUC-4, LINK ha d been used to extract information from free-form texts in two narrow application domains . One application corpus contained terse descriptions of symptoms displayed by malfunctioning automobiles, and the repairs which fixed them . The other corpus described sequences of activities to be performed on an assembly

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... . In empirical testing in these two domains, LINK correctly processed 70% of previously unseen descriptions . A template was counted as correct only if all of the fillers in the template were filled correctly . In addition, LINK generated incomplete (but not incorrect) templates for another 15% of the descriptions . These previous domains were much narrower than the MUC-4 terrorism domain . As a comparison, the lexicons for the previous domains contained only 300-500 words, compared wit h 6700 words in our MUC-4 test configuration . Previous grammar size ranged from 75-100 rules , compared with over 500 rules in the MUC-4 knowledge base . In addition, the previous application domains consisted only of single-sentence inputs . Thus, the integration of information from multiple sentences was not an issue in our previous work .