Role of Dependency Distance in Text Simplification: A Human vs ChatGPT Simplification Comparison

Lee, Sumi, Leroy, Gondy, Kauchak, David, Just, Melissa

arXiv.org Artificial Intelligence 

This study investigates human and ChatGPT text simplification and its relationship to dependency distance. A set of 220 sentences, with increasing grammatical difficulty as measured in a prior user study, were simplified by a human expert and using ChatGPT. We found that the three sentence sets all differed in mean dependency distances: the highest in the original sentence set, followed by ChatGPT simplified sentences, and the human simplified sentences showed the lowest mean dependency distance. Introduction Enhancing the understandability of biomedical information is vital in fostering health-literate patients. However, empirical evidence shows that readability formulas are not appropriate tools [1], [2].

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