Howard University-AI4PC at SemEval-2025 Task 2: Improving Machine Translation With Context-Aware Entity-Only Pre-translations with GPT4o

AbstractThis paper presents our work on a 3-Step GPT translation system developed for SemEval-2025 Task 2 to enhance the translation of named entities within machine translation. Our approach integrates (1) entity extraction via wikidata, (2) GPT-based refinement of entity translations, and (3) final context-aware GPT translation. Results from the original dataset of six languages show significant improvements in the handling of named entities compared to direct GPT-based translation baselines. We further discuss replicability, observed challenges, and outline future research directions.