In this experimental work, we explore Task 2 of the SimpleText Lab, which aims to enhance text simplification technologies using manually annotated datasets. The objective of this work is to propose a methodology for evaluating the capability of Large Language Models to identify and explain difficult terms through optimal prompting. Additionally, we assess improvements by manually correcting the extracted terms and definitions, aiming to refine and advance the utility of text simplification tools for broader applications.
UNIPD@SimpleText2024: A Semi-Manual Approach on Prompting ChatGPT for Extracting Terms and Write Terminological Definitions
Di Nunzio G. M.
;Vezzani F.
2024
Abstract
In this experimental work, we explore Task 2 of the SimpleText Lab, which aims to enhance text simplification technologies using manually annotated datasets. The objective of this work is to propose a methodology for evaluating the capability of Large Language Models to identify and explain difficult terms through optimal prompting. Additionally, we assess improvements by manually correcting the extracted terms and definitions, aiming to refine and advance the utility of text simplification tools for broader applications.
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