Application of AI Technology in Terminology Annotation

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Authors: Yanxia Qin, Zemeng Liu, Ting Wang, Jinwen Zhou
Cited by: 0

Abstract

Accurate terminology annotation is crucial for translators to enhance text processing efficiency and ensure translation quality control.Within the translation workflow, it stands as the most critical step in the pre-translation phase.Terminological competence is an essential "bread-and-butter skill" for professional translators.Traditional terminology annotation methods, reliant on manual experience or rule-based technologies, often suffer from low efficiency and poor accuracy.This teaching case study utilizes petroleum science and technology literature as the source text for terminology annotation activity.It focuses on AIempowered terminology annotation within the translation process, demonstrating how a "teacher-student-machine synergy" adds powerful wings to annotation efficiency.The implementation involves establishing a manual annotation group, and an upgraded human-machine collaborative annotation group.This framework guides students to deeply explore AI-augmented annotation, cultivates their ability for human-machine collaborative and co-creation, and allows them to experience the satisfaction of human-machine win-win outcomes.The ultimate goal is to achieve the practical teaching objective of enhancing students' terminological competence.

Fields of Study & Subjects

Translation Studies and Practices Natural Language Processing Techniques linguistics and terminology studies

Publication details

Journal / source
Advances in economics, business and management research/Advances in Economics, Business and Management Research
Pages
268–278
Publication date
1 January 2026
Language
EN
Document type
Book chapter