AMBIGUITY IN LINGUISTICS1

IF 0.4 3区 文学 0 LANGUAGE & LINGUISTICS
Jordi Fortuny, Lluís Payrató
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引用次数: 0

Abstract

Abstract Ambiguity is conventionally defined in Linguistics as a property of a word or an utterance that has two meanings or two interpretations, and is usually classified as lexical, morphological, syntactic (or structural), and pragmatic. Giving an adequate definition of linguistic ambiguity is not trivial, nor is there unanimity in accepting it. Most researchers tend to agree that ambiguity should be distinguished from related concepts such as vagueness, context sensitivity, reference transfer, and underdetermination or generality of meaning. The distinction between these concepts is also related to the divergences or connections between the perspectives of analysis of ambiguity, and the aim of each work. In this introduction, we define the limits of ambiguity with respect to related concepts and summarize the studies contained within this special issue. These studies do not cover all possible approaches to linguistic ambiguity, but provide a broad overview that can be useful in different fields. We trust that they will contribute to deepening into a phenomenon that is not yet well described and that seems to be consubstantial with the use of language.
语言学中的歧义
在语言学中,歧义通常被定义为一个词或话语具有两种意思或两种解释的特性,通常分为词汇、形态、句法(或结构)和语用。给语言歧义下一个适当的定义不是微不足道的,也不是所有人都接受它。大多数研究者倾向于将歧义与相关概念如模糊、语境敏感、参考迁移、意义的不确定或普遍性等区分开来。这些概念之间的区别也与分析歧义的视角和每件作品的目的之间的分歧或联系有关。在这篇导论中,我们定义了歧义的界限,并就相关概念进行了总结。这些研究并没有涵盖所有可能的语言歧义方法,但提供了一个广泛的概述,可以在不同的领域有用。我们相信,它们将有助于深入研究一种尚未得到很好描述的现象,这种现象似乎与语言的使用是同质的。
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来源期刊
STUDIA LINGUISTICA
STUDIA LINGUISTICA LANGUAGE & LINGUISTICS-
CiteScore
1.20
自引率
0.00%
发文量
21
期刊介绍: Studia Linguistica is committed to the publication of high quality, original papers and provides an international forum for the discussion of theoretical linguistic research, primarily within the fields of grammar, cognitive semantics and language typology. The principal aim is to open a channel of communication between researchers operating in traditionally diverse fields while continuing to focus on natural language data.
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