在关联数据中呈现语义变化

IF 0.9 0 LANGUAGE & LINGUISTICS Languages Pub Date : 2024-06-12 DOI:10.3390/languages9060215
Anas Fahad Khan, Francesca Frontini
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引用次数: 0

摘要

在本文中,我们将介绍一个新的框架--本体论模型(IOM),用于在语言链接数据资源中表示意义,尤其是表示语义变化。该框架利用了词汇语义学和本体论文献中的前人成果,旨在帮助澄清我们对语义变化建模时的含义,并协助我们为此制定不同的本体论模式。在这项工作中,我们假设了一个简单的架构,它是著名的 OntoLex-Lemon 词库的基础,由一个或多个与本体相连的词典组成。我们的模型以这一架构为基础,并借鉴了以前关于词义和本体的研究成果,旨在为静态和动态版本的词义学和语义学变化建模提供清晰的解释。本文介绍了 IOM 框架如何在 "静态 "情况下将词义表示为词与本体概念之间的关系,从而证明 IOM 与 OntoLex-Lemon 是兼容的(同时提供了有关 "意义 "和 "参照 "关系含义的更多细节)。然后,它将详细介绍 IOM 如何帮助我们理解如何对链接数据词法资源中的语义转换进行建模,重点是概念变化和为语义转换数据添加时间信息。
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Toward a Representation of Semantic Change in Linked Data
In this article, we introduce a new framework, the Intensional–Ontological Model (IOM), for representing meaning, and especially for representing semantic change, in linguistic linked data resources. This framework, which makes use of previous work in the literature on lexical semantics and ontologies, is intended to help clarify what we mean when we model semantic change and to assist in elaborating different ontology patterns for doing so. In this work, we assume a simple architecture, one which is at the basis of the well-known OntoLex-Lemon vocabulary and which consists of one or more lexicons linked to an ontology. Our model, which is based on this architecture and informed by previous work on word senses and ontologies, is intended to provide a clear interpretation for the modelling of both onomasiological and semiasological changes, in both static and dynamic versions. This article describes how the IOM framework represents word meaning as the relationship between a word and an ontological concepts in the ’static’ case, demonstrating that the IOM is compatible with OntoLex-Lemon (while at the same time providing a greater level of detail as to the meaning of the ’sense’ and ’reference’ relationships). It then goes on to detail how the IOM can help us understand how to model semantic shifts in linked data lexical resources with a focus on conceptual change and the addition of temporal information to semantic shift data.
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来源期刊
Languages
Languages Arts and Humanities-Language and Linguistics
CiteScore
1.40
自引率
22.20%
发文量
282
审稿时长
11 weeks
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