That’s because prompting machine translations has yielded promising results, and requires these ‘language specialists’ to prompt the model, and analyze the output.
Examples of prompts include defined roles or objectives, such as “act as a professional English-to-Greek translator specialized in healthcare”, or other inferred prompts to refer to information already known to the model.
Research on prompting has led to publications of the most useful prompts for translation and multilingual copy generation, and has sparked discussions on how it can help translation project managers.
Slator Pro Guide: Translation AI
The Slator Pro Guide presents 10 new and impactful ways that LLMs can be used to enhance translation workflows.
The applications of prompting are vast. Possible use cases include prompting for tone of voice, gender-neutral language, creativity, or customer-specific terminology. These opportunities also open new doors for using LLMs to author content with expert-in-the-loop workflows.
Slator’s recently released Pro Guide: Translation AI provides a concise snapshot of the latest practical applications of large language models (LLMs) in translation, and includes a use case on performing machine translation with prompting.
The use case is one of ten, one-page examples of LLMs being put to use, and is drawn from research and interviews with some of the industry’s leading language technology providers.
