中文名词是大量名词信息论计算证明

IF 1.1 3区 文学 0 LANGUAGE & LINGUISTICS Lingua Pub Date : 2024-09-18 DOI:10.1016/j.lingua.2024.103815
Wei Zhou , Guangyan Zhang , Yujie Chen
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引用次数: 0

摘要

普通话中的质数区分在语言学界引起了激烈的争论。以往的研究主要通过定性方法来研究质数区别。我们的研究运用互信息并创造了三种变异条件来探讨汉语名词与分类器个体化功能之间的关系。此外,我们还对 1,000 个 Num-CL-N(数词-分类词-名词)结构实例进行了定量分析,从而检验了质量-数量区别。计算结果表明,分类词的个别化功能受到名词同质性的影响。此外,我们认为汉语名词表现出同质性倾向,名词的深层语义处理类似于类或集合,为语言哲学中的广义质量名词假说和集合名假说提供了证据。
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Chinese nouns are mass nouns: An information-theoretic computational proof

The mass–count distinction in Mandarin Chinese has been heatedly debated in linguistics. Previous research investigated the mass–count distinction primarily through qualitative methods. Our study applied mutual information and created three variation conditions to explore the relationship between Chinese nouns and the individuation function of classifiers. Furthermore, we examined the mass–count distinction by quantitatively analyzing 1,000 instances of Num–CL–N (numeral–classifier–noun) structures. The computational results indicate that the individuation function of classifiers is influenced by noun homogeneity. Moreover, we argue that Chinese nouns exhibit an inclination for homogeneity and the deep semantic processing of nouns is similar to classes or sets, providing evidence for the broad mass noun hypothesis and the collective-name hypothesis in the philosophy of language.

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来源期刊
Lingua
Lingua Multiple-
CiteScore
2.50
自引率
9.10%
发文量
93
审稿时长
24 weeks
期刊介绍: Lingua publishes papers of any length, if justified, as well as review articles surveying developments in the various fields of linguistics, and occasional discussions. A considerable number of pages in each issue are devoted to critical book reviews. Lingua also publishes Lingua Franca articles consisting of provocative exchanges expressing strong opinions on central topics in linguistics; The Decade In articles which are educational articles offering the nonspecialist linguist an overview of a given area of study; and Taking up the Gauntlet special issues composed of a set number of papers examining one set of data and exploring whose theory offers the most insight with a minimal set of assumptions and a maximum of arguments.
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