Towards a unified framework for bilingual terminology extraction of single-word and multi-word terms
Abstract
Extracting a bilingual terminology for multi-word terms from comparable corpora has not been widely researched. In this work we propose a unified framework for aligning bilingual terms independently of the term lengths. We also introduce some enhancements to the context-based and the neural network based approaches. Our experiments show the effectiveness of our enhancements of previous works and the system can be adapted in specialized domains.- Anthology ID:
- C18-1242
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2855–2866
- Language:
- URL:
- https://aclanthology.org/C18-1242
- DOI:
- Cite (ACL):
- Jingshu Liu, Emmanuel Morin, and Peña Saldarriaga. 2018. Towards a unified framework for bilingual terminology extraction of single-word and multi-word terms. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2855–2866, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Towards a unified framework for bilingual terminology extraction of single-word and multi-word terms (Liu et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/naacl24-info/C18-1242.pdf
- Code
- Dictanova/term-eval