Data, information, knowledge, understanding: computing up the meaning hierarchy

This paper discusses computational approaches to computing meaning, arguing that the following four steps are necessary intermediates between the appearance of words in natural language, in whatever medium, and the meaning we want to compute from natural language: pattern detection, information structure creation, knowledge extraction, and application to understanding. It presents computational models for each step as well, in the form of algorithms that detect repetitive or persistent patterns in otherwise unrestricted natural language text, construct information structures from those patterns, extract knowledge from those information structures, and apply the knowledge to problems of understanding situation descriptions obtained in natural language.