Abstract
Idioms exhibit varying degrees of semantic transparency, making their translation challenging. Cross-language differences in idiom usage and connotations add complexity. Using a large language modeling (LLM) approach, we automate Chinese-to-English idiom translation in three steps: (1) Semantic analysis of Chinese idioms using ontology or FrameNet to identify key concepts/relationships like action, purpose, outcome, and context. (2) Generation of multi-word English expressions reflecting these concepts. (3) Selection of the top English idiom candidate that closely matches the Chinese idiom’s meaning. Applied to examples like ‘破釜沉舟’, ‘刀山火海’, and ‘抛砖引玉’, our method performs on par with human experts. The semantic reasoning approach enhances transparency in LLM decisions, simulating logical inferences over the semantic framework.- Anthology ID:
- 2024.amta-presentations.7
- Volume:
- Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 2: Presentations)
- Month:
- September
- Year:
- 2024
- Address:
- Chicago, USA
- Editors:
- Marianna Martindale, Janice Campbell, Konstantin Savenkov, Shivali Goel
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 95–115
- Language:
- URL:
- https://aclanthology.org/2024.amta-presentations.7
- DOI:
- Cite (ACL):
- Ming Qian. 2024. Automating Idiom Translation with Cross-Lingual Natural Language Generation Grounded In Semantic Analyses Using Large Language Models. In Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 2: Presentations), pages 95–115, Chicago, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Automating Idiom Translation with Cross-Lingual Natural Language Generation Grounded In Semantic Analyses Using Large Language Models (Qian, AMTA 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.amta-presentations.7.pdf