中国科技术语 ›› 2023, Vol. 25 ›› Issue (2): 44-50.doi: 10.12339/j.issn.1673-8578.2023.02.006

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面向翻译的语言知识服务系统构建——核心结构与基本原则

宁海霖()   

  1. 天津商业大学外国语学院,天津 300134
  • 收稿日期:2022-09-29 修回日期:2023-03-14 出版日期:2023-04-05 发布日期:2023-03-31
  • 作者简介:

    宁海霖(1982—),男,博士,天津商业大学外国语学院讲师,研究方向为术语学与翻译技术。2016年维也纳国际术语学暑期学校学员,教育部人文社会科学基金项目主持人,参与国家社会科学基金重大项目、全国翻译专业学位研究生教育研究项目各1 项,在《中国翻译》《中国科技翻译》《翻译界》《中国科技术语》等期刊发表论文10 余篇。通信方式:

  • 基金资助:
    教育部人文社会科学研究青年基金项目“翻译技术的知识化演进模式研究”(18YJC740067)

Fundamental Layers and Designing Principles of Language-Knowledge Service System for Translational Purposes

NING Hailin()   

  • Received:2022-09-29 Revised:2023-03-14 Online:2023-04-05 Published:2023-03-31

摘要:

面向翻译的语言知识服务系统将平行语料库、术语库、本体知识库等语言知识资源统一整合,在此基础上对资源进行客观、直观、动态的描写,挖掘重要语言特征与知识结构,建立知识系统,并通过可视化手段对描述的结果进行形象化表征,提高认知效率与工作效率,满足翻译生态系统内部各个重要环节的知识应用需求和协同创新需求。语言知识服务系统的建设过程遵循协同化、统一化、可视化三原则,其核心部分由基础层、分析层与应用层三部分构成,分别负责语言资源供给、数据分析统计与知识表征运用,形成了模块融合共通、知识循环利用的交互式有机整体。

关键词: 语言知识服务系统, 资源描述, 多模态, 知识习得, 机器翻译

Abstract:

The language-knowledge service system for translational purposes is an organic integration of parallel corpora, term banks and ontological knowledge bases. The system is designed towards the achievement of two major functions, through which both wanted knowledge and coordinated innovation in the entire translational ecosystem are accessible: (1) the objective, intuitive and processive resource description aiming at knowledge discovery and construction; (2) visualization of the organized data aiming at the enhancement of cognitive capacity and working efficiency. As a product of collaboration, standardization and visualization, the system structures its kernel section with three layers, named the elementary, the analytical, and the applied layer. The elementary layer firstly delivers basic language resources to the analytical layer, then the processed resources and relative results are transported to the applied layer for visualized representation, thus an interactive system of module connecting and knowledge recycling is composed accordingly.

Key words: language-knowledge service system, resource description, multi-modality, knowledge acquisition, machine translation

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