论文标题
gispy：一种用于测量文本中要点推理得分的工具
GisPy: A Tool for Measuring Gist Inference Score in Text
论文作者
论文摘要
决策理论（例如模糊迹象理论（FTT））表明，在做出决策时，个人倾向于在文本中依靠观点或底线含义。在这项工作中，我们描述了开发Gispy的过程，Gispy是Python中用于测量文本中要点推理得分（GIS）的开源工具。对新闻和科学文本领域三个基准的文档的Gispy评估表明，我们的工具产生的分数显着区分了低观点和高要素文档。我们的工具可公开使用：https：//github.com/phosseini/gispy。
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.
