Abstract
A system is described which digests large volumes of text, filtering out irrelevant articles and distilling the remainder into templates that represent information from the articles in simple slot/filler pairs. The system is highly modular in that it consists of a series of programs, each of which contributes information to the text to help in the final analysis of determining which strings constitute valid values for the slots in the template. This modular design has the dual advantage of allowing relatively easy debugging and of permitting many of the component programs to participate in other projects. The system is customized to specific domains, taking advantage of simple string matching techniques to improve the effectiveness of more complex sentence-level semantic processes. The extension to new domains has been facilitated by dividing system data files into generic vs. specific categories; domain extension requires the creation of only the domain-specific files. © 1993 John Wiley & Sons, Inc.
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