TurkMedNLI: a Turkish medical natural language inference dataset through large language model based translation.

ABSTRACT: Natural language inference (NLI) is a subfield of natural language processing (NLP) that aims to identify the contextual relationship between premise and hypothesis sentences. While high-resource languages like English benefit from robust and rich NLI datasets, creating similar datasets for low-resource languages is challenging due to the cost and complexity of manual annotation. Although translation of existing datasets offers a practical solution, direct translation of domain-specific datasets presents unique challenges, particularly in handling abbreviations, metric conversions, and cultural alignment. This study introduces a pipeline for translating a medical NLI dataset into Turkish, which is a low-resource language. Our approach employs fine-tuning the Llama-3.1 model with selected s

SUBMITTER: Ogul IU 

PROVIDER: S-EPMC11888880 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature