使用SMT求解器进行风险分析:检测文本中的逻辑错误

Florence Dupin de Saint-Cyr -- Bannay, M. Lagasquie-Schiex, W. Raynaut, P. Saint-Dizier
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引用次数: 1

摘要

本文的目的是描述LELIE项目的一些结果,这些结果是人工智能对一个特殊领域的贡献:分析由于编写不良的技术文档而导致的风险。这是一个多学科的贡献,因为它结合了自然语言处理和逻辑满意度检查。本文解释了可满足性检查如何用于检测程序文本中的不一致、冗余和不完整,并描述了实现的工具产生技术文本的逻辑翻译和实现检查的部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using a SMT Solver for Risk Analysis: Detecting Logical Mistakes in Texts
The purpose of this paper is to describe some results of the LELIE project, that are a contribution of Artificial Intelligence to a special domain: the analysis of the risks due to poorly written technical documents. This is a multidisciplinary contribution since it combines natural language processing with logical satisfiability checking. This paper explains how satisfiability checking can be used for detecting inconsistencies, redundancy and incompleteness in procedural texts and describes the part of the implemented tool that produces the logical translation of technical texts and realizes the checkings.
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