The senses of words evolve. The sense of the same word may change from today to tomorrow, and multiple senses of the same word may be the result of the evolution of each other, that is, they may be parents and children. If we view Juba as an evolving ecosystem, the paradigm of learning the correct answer, which does not move with the sense of a word, is no longer valid. This paper is a case study that shows that word polysemy is an evolutionary consequence of the modification of Semantic Cells, which has al-ready been presented by the author, by introducing a small amount of diversity in its initial state as an example of analyzing the current set of short sentences. In particular, the analysis of a sentence sequence of 1000 sentences in some order for each of the four senses of the word Spring, collected using Chat GPT, shows that the word acquires the most polysemy monotonically in the analysis when the senses are arranged in the order in which they have evolved. In other words, we present a method for analyzing the dynamism of a word's acquiring polysemy with evolution and, at the same time, a methodology for viewing polysemy from an evolutionary framework rather than a learning-based one.

翻译：词义会随时间演化。同一词汇的含义可能从今日到明日发生变化，而同一词汇的多种义项可能是彼此演化的结果，即可能存在亲代与子代关系。若将语言视为动态演化的生态系统，传统基于固定正确答案的学习范式——其不随词义演化而调整——将不再适用。本文通过案例研究证明，词汇多义性是语义单元（Semantic Cells）初始状态引入微量多样性后发生演化的结果，该语义单元模型已由作者先前提出。研究以当前短句集分析为例，特别针对"Spring"一词的四种义项，使用Chat GPT收集并按特定顺序排列的1000句序列进行分析。结果表明：当义项按演化先后顺序排列时，该词汇在分析中呈现单调递增的多义性获取趋势。本研究由此提出一种分析词汇多义性动态演化机制的方法，同时构建了从演化框架（而非基于学习的框架）审视多义性现象的方法论体系。