In <cite>Clark and Curran (2004)</cite> we show that using this more restrictive setting has a small negative impact on the accuracy of the resulting parser (about 0.6 F-score over labelled dependencies). However, the memory requirement for training the model is now only 4 GB, a reduction of 87% compared with the original approach.