Customer data typically is held in database systems, which can be seen as rule-based knowledge base, whereas businesses increasingly want to benefit from the capabilities of large, pre-trained language models. In this technical report, we describe a case study of how a commercial rule engine and an integrated neural chatbot may be integrated, and what level of control that particular integration mode leads to. We also discuss alternative ways (including past ways realized in other systems) how researchers strive to maintain control and avoid what has recently been called model "hallucination".

翻译：客户数据通常存储在数据库系统中，这可被视为基于规则的知识库，而企业日益期望从大规模预训练语言模型的能力中获益。本技术报告描述了一个案例研究，探讨了商业规则引擎与集成式神经聊天机器人如何实现整合，以及这种特定整合模式所能带来的控制程度。我们还讨论了研究人员为维持控制并避免近期所称的模型"幻觉"问题而采用的其他替代方法（包括其他系统中先前实现的方法）。