Bridging the Gap Between Schank and Montague

Documents that people write to communicate with other people are rarely as precise as a formal logic. Yet people can read those documents and relate them to formal notations for science, mathematics, and computer programming. They can derive whatever information they need, reason about it, and apply it at an appropriate level of precision. Unlike theorem provers, people rely on analogies for their reasoning. Even mathematicians use analogies to discover their theorems and formal proofs to verify and codify their discoveries. This article shows how a high-speed analogy engine is used to analyze natural language texts and relate the results to both structured and unstructured representations. The degree of precision in the results depends more on the precision in the knowledge sources used to analyze the documents than on the precision of the language in the documents themselves.