GisPy: A Tool for Measuring Gist Inference Score in Text
This provides a tool for researchers in psychology and computational linguistics to quantify gist in text, but it is incremental as it builds on existing theories like Fuzzy-Trace Theory.
The researchers tackled the problem of measuring gist inference in text by developing GisPy, an open-source Python tool, and found that it significantly distinguishes low vs. high gist documents across three benchmarks from news and scientific text domains.
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.