For an “intelligent” system to describe a real-world situation using as few statements as possible, it is necessary to make inferences based on observed data and to incorporate general knowledge of the reasoning domain into the description. These reasoning processes must reduce several levels of specific descriptions into only those few that most precisely describe the situation. Moreover, the system must be able to generate descriptions in the absence of data, as instructed by certain rules of inference. The deductions applied by the system, then, generate a high-level description from the low-level evidence provided by the real and default data sources. We describe an implementation of these ideas in a real-world situation. The application concerns evaluation of Space Shuttle electromechanical system configurations by console operators in the Mission Control Center. A production system provides the reasoning mechanism through which the default assignments and specializations occur. We provide examples within this domain for each type of inference, and discuss the suitability of each toward achieving our goal of describing a situation in the fewest statements possible. Finally, we suggest several enhancements that will further increase the intelligence of similar spacecraft monitoring applications.