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This paper describes CBAS, a data extraction system with rule-based reasoning modules. The CBAS architecture depicted in Figure 1 emphasizes the use of multiple processors to detect significant primitive facts which are then processed by reasoning modules implemented as collections of forward-chaining rules to infer additional information. A guiding principle behind the architecture is to rely as much as possible on initial processors with relatively simple internal structure in order to insure greater robustness. However, the model does allow for the use of sophisticated initial processors, processors which embody linguistic analysis techniques. This emphasis on collections of multiple preprocessors which provide sets of primitive facts to be reasoned about is reminiscent of the standard architecture proposed for multisensor data fusion systems (where preprocessor = sensor) [5].