Abstract
In this paper we describe and evaluate different statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input semantics. Three models are trained and tested; an n-gram language model, a discriminative maximum entropy model using structural features, and a combination of these two. Our realization component forms part of a larger, hybrid MT system.- Anthology ID:
- 2005.mtsummit-papers.15
- Volume:
- Proceedings of Machine Translation Summit X: Papers
- Month:
- September 13-15
- Year:
- 2005
- Address:
- Phuket, Thailand
- Venue:
- MTSummit
- SIG:
- Publisher:
- Note:
- Pages:
- 109–116
- Language:
- URL:
- https://aclanthology.org/2005.mtsummit-papers.15
- DOI:
- Cite (ACL):
- Erik Velldal and Stephan Oepen. 2005. Maximum Entropy Models for Realization Ranking. In Proceedings of Machine Translation Summit X: Papers, pages 109–116, Phuket, Thailand.
- Cite (Informal):
- Maximum Entropy Models for Realization Ranking (Velldal & Oepen, MTSummit 2005)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/2005.mtsummit-papers.15.pdf