@inproceedings{aryal-agyemang-prempeh-2025-howard,
title = "{H}oward {U}niversity-{AI}4{PC} at {S}em{E}val-2025 Task 2: Improving Machine Translation With Context-Aware Entity-Only Pre-translations with {GPT}4o",
author = "Aryal, Saurav and
Agyemang - Prempeh, Jabez",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.246/",
pages = "1885--1889",
ISBN = "979-8-89176-273-2",
abstract = "This 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."
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<abstract>This 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.</abstract>
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%0 Conference Proceedings
%T Howard University-AI4PC at SemEval-2025 Task 2: Improving Machine Translation With Context-Aware Entity-Only Pre-translations with GPT4o
%A Aryal, Saurav
%A Agyemang - Prempeh, Jabez
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F aryal-agyemang-prempeh-2025-howard
%X This 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.
%U https://aclanthology.org/2025.semeval-1.246/
%P 1885-1889
Markdown (Informal)
[Howard University-AI4PC at SemEval-2025 Task 2: Improving Machine Translation With Context-Aware Entity-Only Pre-translations with GPT4o](https://aclanthology.org/2025.semeval-1.246/) (Aryal & Agyemang - Prempeh, SemEval 2025)
ACL