TL;DR
It is argued that neither source alone offers a complete solution, and effective legal translation workflows require the complementary use of LLMs for speed and adaptability, corpora for terminological precision and evidential transparency, and expert human judgment for authority.
The study concludes that terminological consistency should be considered as a separate dimension of translation quality and emphasizes the importance of terminology control and human post-editing in AI-assisted political translation.
Legal formulae are fixed expressions that can pose several translation challenges in view of system-related peculiarities, especially in international and multicultural settings such as the European Union. General bilingual dictionaries are often used by students and translators to cope with legilinguistic hurdles, alt...
This study evaluates the performance of three machine translation tools: ChatGPT (OpenAI GPT-3.5, March 2024), Google Translate (web version, April 2024), and DeepL (free web version, April 2024), focusing on a corpus of Algerian Supreme Court judgments.
This study investigates the register variation in texts written by humans and comparable texts produced by large language models (LLMs). Multidimensional analysis (MDA) is applied to a sample of human-written texts and AI-generated counterpart texts to find the dimensions of variation in which LLMs differ most si...
This work introduces the first-of-its-kind English-Assamese parallel corpus for the translation of Indian court judgments and performs a comprehensive evaluation of state-of-the-art multilingual models in both zero-shot and fine-tuned settings, comparing their performance against commercial systems.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
