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as an evolving ecosystem, the paradigm of learning the correct answer, which does not move with the sense of a word, is no longer valid.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：词义会随时间演变。同一词汇的语义可能朝夕相异，其多种义项常互为演化结果，形成亲代与子代的传承关系。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——即脱离词义演变轨迹的静态认知模式——将不再适用。本文通过案例研究，论证词汇多义性实为语义单元（作者先前提出的理论模型）在初始状态引入微量多样性后演化产生的结果，并以当前短句集的分析为例进行阐释。具体而言，我们利用Chat GPT收集包含"Spring"四种义项的1000个有序例句序列进行分析，结果表明：当义项按演化时序排列时，该词汇在分析过程中呈现单调递增的多义性获取特征。本研究由此提出一种基于演化框架（而非传统学习框架）的分析方法，既可解析词汇多义性随演化的动态获取机制，亦为从演化视角审视多义现象提供了方法论基础。