A framework for truth and honesty in large language processing for safety engineering

The work presented here had its origin in the 1970’s [7] when it was shown that a significant fraction of incidents and minor accidents in nuclear plant arose due to errors in operating procedures. Methods were developed for translating operating procedures to a form which supported simulation, allowing detection of errors and omissions automatically [7]. Since then, the methods have been used for quality assurance of risk analyses and safety engineering for over 100 large process plants [9, 13]. This paper describes the development of a framework for a use of grammatical and semantic rule-based methods to support large language models is a way that allows true and honest answers to questions and requests posed, and its implementation in a program, Cassandra, developed by the author.