Paper: Statistical Ranking In Tactical Generation

ACL ID W06-1661
Title Statistical Ranking In Tactical Generation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006

In this paper we describe and evaluate several statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input se- mantics. Three models (and several vari- ants) are trained and tested: an D2-gram language model, a discriminative maxi- mum entropy model using structural in- formation (and incorporating the language model as a separate feature), and finally an SVM ranker trained on the same feature set. The resulting hybrid tactical generator is part of a larger, semantic transfer MT system.