THM@SimpleText 2025——任务1.1：针对非专家基于复杂术语重新审视文本简化
THM@SimpleText 2025 -- Task 1.1: Revisiting Text Simplification based on Complex Terms for Non-Experts
AI总结：
针对科学文本因技术术语导致的复杂性问题，本研究聚焦SimpleText 2025任务1.1中极短语境下复杂句子的简化，通过识别复杂术语并利用小型Gemini和OpenAI大语言模型为非专家重新表述，提升科学信息的可获取性。
摘要：
科学文本本质上包含技术术语，因此较为复杂。为非领域专家简化此类文本可提升创新成果与信息的可获取性：政治家能理解其拟立法议题的新发现，重病患者家属可阅读临床试验相关内容。SimpleText CLEF实验室正是聚焦于这一科学文本简化问题。2025年版的任务1.1专门处理复杂句子的简化，即语境极少的极短文本。为解决该任务，我们研究了句子中复杂术语的识别，并使用小型Gemini和OpenAI大型语言模型为非专家读者重新表述这些术语。
英文摘要：
Scientific text is complex as it contains technical terms by definition. Simplifying such text for non-domain experts enhances accessibility of innovation and information. Politicians could be enabled to understand new findings on topics on which they intend to pass a law, or family members of seriously ill patients could read about clinical trials. The SimpleText CLEF Lab focuses on exactly this problem of simplification of scientific text. Task 1.1 of the 2025 edition specifically handles the simplification of complex sentences, so very short texts with little context. To tackle this task we investigate the identification of complex terms in sentences which are rephrased using small Gemini and OpenAI large language models for non-expert readers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
