In this paper, we address the problem of giving names to predicates in logic rules using Large Language Models (LLMs). In the context of Inductive Logic Programming, various rule generation methods produce rules containing unnamed predicates, with Predicate Invention being a key example. This hinders the readability, interpretability, and reusability of the logic theory. Leveraging recent advancements in LLMs development, we explore their ability to process natural language and code to provide semantically meaningful suggestions for giving a name to unnamed predicates. The evaluation of our approach on some hand-crafted logic rules indicates that LLMs hold potential for this task.

翻译：本文探讨了利用大型语言模型为逻辑规则中的谓词赋予名称的问题。在归纳逻辑编程的背景下，多种规则生成方法会产生包含未命名谓词的规则，其中谓词发明是一个关键示例。这阻碍了逻辑理论的可读性、可解释性和可重用性。借助大型语言模型发展的最新进展，我们探索其处理自然语言和代码的能力，从而为未命名谓词提供具有语义意义的命名建议。在部分手工构建的逻辑规则上对我们方法的评估表明，大型语言模型在此任务中具有潜力。