%0 Journal Article
%T 中国特色法律翻译术语库建设初探——以新《公司法》英译为例
A Preliminary Exploration of the Construction of a Legal Terminology Database with Chinese Characteristics—A Case Study of the English Translation of the Revised Company Law
%A 张格鸣
%A 刘甜
%A 夏涵
%J Modern Linguistics
%P 582-592
%@ 2330-1716
%D 2025
%I Hans Publishing
%R 10.12677/ml.2025.134386
%X 本文以构建中国特色法律翻译术语库为核心目标,以2024年施行的新《公司法》英译为实践案例,探讨法律术语库建设的路径与方法。本研究通过对比国内外术语库建设现状,发现国内存在技术滞后、数据孤岛化及跨学科协作不足等问题。为此,本文提出术语库的搭建框架,并强调需遵循国家标准与用户需求导向的系统设计。在实践层面,采用ChatGPT辅助提取新《公司法》术语,结合Multiterm工具构建单机版术语库,并规划基于前后端技术的在线平台开发方案。研究验证了人工智能与术语管理工具协同的可行性,为后续规模化建设提供了方法论支持。
This study centers on the construction of a legal terminology database with Chinese characteristics, employing the English translation of the 2024 revised Company Law as a practical case investigation to explore pathways and methodologies for legal terminology repository development. This study, through a comparison of the current situations of terminology database construction at home and abroad, has found that there are such problems as technical lag, data isolation, and insufficient interdisciplinary collaboration in China. To this end, this paper proposes a framework for the construction of the terminology database, emphasizing the necessity of adhering to national standards and a user-oriented system design. At the practical implementation level, this research employs ChatGPT-assisted terminology extraction from the 2024 revised Company Law, integrates the Multiterm tool for standalone database compilation, and outlines a development framework for an online platform incorporating front-end and back-end technological architectures. This study has verified the feasibility of the collaboration between artificial intelligence and terminology management tools, providing methodological support for the subsequent large-scale construction.
%K 国际话语权,
%K 法律术语库,
%K 术语库框架,
%K 术语提取
International Discourse Power
%K Legal Terminology Database
%K Terminology Database Framework
%K Terminology Extraction
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=112830