Abstract
Natural language semantic engineering problems are faced with unknown input and intensive knowledge challenges. In order to adapt to the featuresof natural language semantic engineering, the AI programinglanguage needs to be expanded mathematically: 1) Using many ways to improve the spatial distribution and coverage of instances; 2) Keeping different abstract function versions running at the same time; 3) Providing a large numberof knowledge configuration files and supporting functions to deal with intensive knowledge problems; 4) Using the most possibilitypriority call to solve the problem of multiple running branchestraversal. This paper introduces the unknown oriented programming ideas, basic strategy formulation,language design and simulation running examples. It provides a new method for the incremental research and development of large-scale natural language semantic engineeringapplication. Finally, this paper summarizes the full text and puts forward the further research direction.
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