Application of AI Technology in Terminology Annotation
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