Decision making theories such as Fuzzy-Trace Theory (FTT) suggest that individuals tend to rely on gist, or bottom-line meaning, in the text when making decisions. In this work, we delineate the process of developing GisPy, an open-source tool in Python for measuring the Gist Inference Score (GIS) in text. Evaluation of GisPy on documents in three benchmarks from the news and scientific text domains demonstrates that scores generated by our tool significantly distinguish low vs. high gist documents. Our tool is publicly available to use at: https://github.com/phosseini/GisPy.

翻译：诸如Fuzzy-Trace理论(FTT)等决策理论表明,个人在做决定时往往依赖文字中的亮点或底线意义。在这项工作中,我们界定了开发GisPy的过程,GisPy是Python的一个公开来源工具,用于测量文本中的Gist推论分数。GisPy对新闻和科学文本领域三个基准文件的评价表明,我们工具产生的分数显著区别了低比高基词文件。我们的工具在https://github.com/phosseini/GisPy上公开使用。