We present log-linear models for use in the tasks of parse disambiguation and realisation ranking in German. Forst (2007a) shows that by extending the set of features used in parse disambiguation to include more linguistically motivated information, disambiguation results can be significantly improved for German data. The question we address in this paper is to what extent this improved set of features can also be used in realisation ranking. We carry out a number of experiments on German newspaper text. In parse disambigua- tion, we achieve an error reduction of 51%, compared to an error reduction of 34.5% with the original model that does not include the additional fea- tures of Forst (2007a). In realisation ranking, BLEU score increases from 0.7306 to 0.7939, and we achieve a 10 point improvement in exact match over a baseline language model. This being said, our results also show that further features need to be taken into account for realisation ranking in order to improve the quality of the corresponding model.