Enriching Knowledge Representation of Terminology

IF 0.8 2区 文学 0 LANGUAGE & LINGUISTICS International Journal of Lexicography Pub Date : 2022-06-08 DOI:10.1558/lexi.20443
Yi Peng, Bei-Bei Luo, Chenxing Xiao
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Abstract

Whereas a number of studies have been conducted towards representing knowledge linked with terms, terminological knowledge still demands further exploration due to its diversity and intricacy. Although much recent cognitive terminological research has examined either frames or event structures based on specialized contexts and hence has helped improve the clarification of relevant knowledge representation, other types of knowledge structures tied to terms like metaphoric and metonymic structures as well as conceptual blending processes of terms have not yet been adequately investigated. In view of this gap, we put forward a cognitive integrated model (CIM), attempting to integrate cognitive structures and construction of terms in a holistic manner. In this study, we mainly center on integration of the decontextualized part: the adapted (ECM1), conceptual metaphor (CM1), conceptual metonymy (CM2), and conceptual blending (CB1) in light of terminological definitions without context, acting as offline knowledge of terms. Integration of the contextualized part is briefly discussed, merely about the adjusted ECM within context (ECM2) as online knowledge. The tentative incorporation of both offline and online knowledge of terms derives at least five particular variants of the CIM: ECM1+ECM2, ECM1+CB1+ECM2, ECM1+CM1+CB1+ECM2, ECM1+CM2+CB1+ECM2, ECM1+CM1+CM2+CB1+ECM2. Accordingly, both definition-based and usage-based methods are exploited, respectively backed up by dictionaries or professional works and corpora, etc. We subsequently apply the five variants to representing Event-Domain Cognitive Model knowledge of international trade terms previously seldom explored in terminology. It turns out that the cognitive integrated perspective contributes to enriching knowledge representation of the terms by exposing diverse knowledge structures and conceptual construction.
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丰富术语的知识表示
术语知识的多样性和复杂性使得术语知识的表达还有待于进一步的探索。尽管最近的许多认知术语研究已经基于专门的语境检查了框架或事件结构,从而有助于改善相关知识表示的澄清,但与术语相关的其他类型的知识结构,如隐喻和转喻结构以及术语的概念混合过程尚未得到充分的研究。鉴于这一差距,我们提出了一个认知整合模型(CIM),试图将认知结构和术语构建整体地整合起来。在本研究中,我们主要关注非语境化部分:适应(ECM1)、概念隐喻(CM1)、概念转喻(CM2)和概念混合(CB1)在没有语境的术语定义下的整合,作为术语的离线知识。本文对情境化部分的整合进行了简要讨论,仅讨论了作为在线知识的情境中调整后的ECM (ECM2)。离线和在线术语知识的试试性结合产生了CIM的至少五种特定变体:ECM1+ECM2, ECM1+CB1+ECM2, ECM1+CM1+CB1+ECM2, ECM1+CM2+CB1+ECM2, ECM1+CM1+CM2+CB1+ECM2。因此,基于定义的方法和基于用法的方法都被利用,分别由词典或专业著作和语料库等来支持。随后,我们应用这五种变体来表示以前很少在术语中探索的国际贸易术语的事件域认知模型知识。结果表明,认知整合视角通过揭示不同的知识结构和概念建构,有助于丰富术语的知识表征。
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来源期刊
CiteScore
1.90
自引率
20.00%
发文量
16
期刊介绍: The International Journal of Lexicography was launched in 1988. Interdisciplinary as well as international, it is concerned with all aspects of lexicography, including issues of design, compilation and use, and with dictionaries of all languages, though the chief focus is on dictionaries of the major European languages - monolingual and bilingual, synchronic and diachronic, pedagogical and encyclopedic. The Journal recognizes the vital role of lexicographical theory and research, and of developments in related fields such as computational linguistics, and welcomes contributions in these areas.
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