中国科技术语 ›› 2024, Vol. 26 ›› Issue (3): 31-37.doi: 10.12339/j.issn.1673-8578.2024.03.004

• 中医药术语研究专题 • 上一篇    下一篇

《黄帝内经·素问》汉法双语平行术语库的构建路径与方法

田知灵(), 许明()   

  1. 北京语言大学,北京 100083
  • 收稿日期:2024-05-09 修回日期:2024-05-27 出版日期:2024-07-05 发布日期:2024-07-05
  • 通讯作者:

    许明(1979—),男,北京语言大学教授,博士生导师。研究方向为翻译学、术语学。主持国家社科项目2项;主持教育部、北京市等省部级课题5项;出版中法文专著4部,编著多部;发表论文20余篇。通信方式:
  • 作者简介:

    田知灵(2000—),女,北京语言大学硕士研究生。研究方向为跨学科翻译研究。通信方式:

Approach and Methods for Constructing Bilingual Parallel Terminology Database of Huangdi Neijing Suwen

TIAN Zhiling(), XU Ming()   

  • Received:2024-05-09 Revised:2024-05-27 Online:2024-07-05 Published:2024-07-05

摘要:

国家对于术语标准化的推动以及文化传播的需求促进了中医术语的翻译与研究,中医术语库的建设也因此走向快车道。但是基于古汉语的汉英、汉法等多语言术语库的建设尚不足,需要在不断摸索中逐渐完善。文章以《黄帝内经·素问》汉法双语语料为研究基础,重点探索借助术语自动提取工具构建双语平行术语库的路径与方法。依托memoQ及TBX术语管理系统设计了两种术语提取方案,探究了提取古汉语—法语双语平行术语过程中遇到的问题,并深入分析了由此构建的汉法平行术语库的术语特征和翻译方法,以期为双语术语库的建设提供新的借鉴与思路。

关键词: 《黄帝内经·素问》, 双语平行术语库, 术语自动提取

Abstract:

The promotion of national standardization of terminology and the demand for cultural dissemination have facilitated the translation and research of Chinese medicine terminology, and the construction of Chinese medicine terminology databases has been on the fast track. However, the construction of multilingual terminology databases based on classical Chinese is still insufficient, which needs to be gradually improved in the course of continuous exploration. Based on the Chinese-French bilingual corpus of Huangdi Neijing Suwen, the present paper focuses on exploring the approach and methods of constructing a bilingual parallel terminology database with the help of the automatic term extraction tools. The article explores the problems and difficulties encountered in the process of extracting classical Chinese-French parallel terms relying on memoQ and TBX terminology management system, and analyzes in depth the terminological features and translation methods of the terminology database constructed as a result, with a view to providing new references and ideas for the construction of bilingual terminology database.

Key words: Huangdi Neijing Suwen, bilingual parallel terminology database, terminology extraction