A framework for truth and honesty in large language processing for safety engineering
Year: 2025
Type: conference-paper
Abstract: 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.
Source: MATEC Web of Conferences
Author: John Robert Taylor
Institution: University of Southern Denmark
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414708819