Terminotics

Teacher(s)

Zilio Leonardo;

Language

French

Prerequisites

·         Basic familiarity with the Microsoft Office suite
·         Mastery of Windows Document Map
Mastery of the basics of theTrados suite (particularly creation of terminology databases with MultiTerm, creation of translation memories with WorkBench)

Main themes

·         Extracting terminology: principles and stages, extraction strategies, overview of current tools
·         Deeper familiarity with one specific tool for terminology extraction
Introduction to MultiTrans, a new tool for terminology management, corpus management and computer-aided translation

Learning outcomes

At the end of this learning unit, the student is able to :
1	Contribution of teaching unit to learning outcomes assigned to programme This unit contributes to the acquisition and development of the following learning outcomes, as assigned to the Master's degree in translation : 2.7, 2.8 4.7 8.5 AA-FS-TL.To develop expertise and a high level of competence in the fields of terminology, terminotics, localisation, technical writing, and project management in translation and localisation, in order to be able to engage effectively in language service provision of this type. Specific learning outcomes on completion of teaching unit On completing this unit the student is able to: ·         Understand the key concepts of terminology and determine their relevance in the context of different projects; ·         Deal with the complexity of a new CAT tool and/or terminology management tool, identifying and resolving any problems; ·         Create, maintain and get the most out of a MultiTrans terminology database, while being able to extract terminology with different tools; ·         Keep up to date with new technological advances, understanding the benefits and limitations of tools, as well as their impact on the work of translators and terminologists.

Content

This module aims at teaching students the use of tools for automated terminology extraction, as well as terminology management.
By means of theoretical explanations mixed with hands-on exercises, students will have the opportunity to learn how to operate different tools, from simple key-word extractors (e.g. Sketch Engine) to more complex pattern-based methods and prompt-based extraction using generative artificial intelligence, and evaluate their results.

Teaching methods

Interactive and expository lectures associated with practical exercises.

Evaluation methods

Sessions in January and August/September: assessment in the form of a written piece of work. Information regarding practical details of the work will be made available during the module and on Moodle.

Other information

/

Online resources

/

Bibliography

/

Faculty or entity

> LSTI