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    <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.</abstract>
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%0 Conference Proceedings
%T Maximum Entropy Models for Realization Ranking
%A Velldal, Erik
%A Oepen, Stephan
%S Proceedings of Machine Translation Summit X: Papers
%D 2005
%8 sep 13 15
%C Phuket, Thailand
%F velldal-oepen-2005-maximum
%X 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.
%U https://aclanthology.org/2005.mtsummit-papers.15
%P 109-116

Markdown (Informal)

[Maximum Entropy Models for Realization Ranking](https://aclanthology.org/2005.mtsummit-papers.15) (Velldal & Oepen, MTSummit 2005)

• Maximum Entropy Models for Realization Ranking (Velldal & Oepen, MTSummit 2005)

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.