Feature-listing tasks are an invaluable resource for exploring how words, categories, and metaphors are represented. However, manually coding the generated features is time-consuming and expensive, and involves subjective judgments from the experimenter. The purpose of this paper is to introduce the “RK processor”, a program that was developed in our lab to analyse metaphor feature data but which can also be applied to other feature-listing data. After detailing the steps of processing, we demonstrate that the processed feature data align with previous findings in which metaphor features were processed manually and that the processed features predict dimensions of metaphor judgments pertaining to comprehensibility and metaphor goodness. Lastly, we present several other applications for research on word similarity, compound words, categories and concepts, semantic ambiguity, incongruity resolution and computational modelling. The RK processor offers researchers a valuable tool to save time and resources and to maintain consistency in processing.

特征列表任务是探索单词、类别和隐喻如何表示的宝贵资源。然而，手动编码生成的特征既耗时又昂贵，并且涉及到实验者的主观判断。本文的目的是介绍“RK 处理器”，这是我们实验室开发的一种程序，用于分析隐喻特征数据，但也可以应用于其他特征列表数据。在详细说明了处理步骤之后，我们证明了处理后的特征数据与先前手动处理隐喻特征的发现一致，并且处理后的特征预测了与可理解性和隐喻善度相关的隐喻判断的维度。最后，我们介绍了其他几个用于研究单词相似性、复合词、类别和概念、语义歧义、不一致解决和计算建模。RK 处理器为研究人员提供了一种宝贵的工具，可以节省时间和资源并保持处理的一致性。