Analyzing Polysemy Evolution Using Semantic Cells

Fuente: arXiv
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Autori principali: Ohsawa, Yukio, Xue, Dingming, Sekiguchi, Kaira
Natura: Preprint
Pubblicazione: 2024
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author Ohsawa, Yukio
Xue, Dingming
Sekiguchi, Kaira
author_facet Ohsawa, Yukio
Xue, Dingming
Sekiguchi, Kaira
contents 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as an evolving ecosystem, the paradigm of learning the correct answer, which does not move with the sense of a word, is no longer valid.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.
format Preprint
id arxiv_https___arxiv_org_abs_2407_16110
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Analyzing Polysemy Evolution Using Semantic Cells
Ohsawa, Yukio
Xue, Dingming
Sekiguchi, Kaira
Computation and Language
Artificial Intelligence
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as an evolving ecosystem, the paradigm of learning the correct answer, which does not move with the sense of a word, is no longer valid.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.
title Analyzing Polysemy Evolution Using Semantic Cells
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2407.16110