GisPy: A Tool for Measuring Gist Inference Score in Text

TL;DR

GisPy is an open-source Python tool designed to measure Gist Inference Score in texts, helping to distinguish between low and high gist documents based on decision-making theories.

Contribution

This work introduces GisPy, the first tool for quantifying gist inference in text, validated across news and scientific domains.

Findings

GisPy scores significantly differentiate low vs. high gist documents

The tool performs well across multiple benchmark datasets

GisPy is publicly available for research use

Abstract

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.