We use the original data and the original implementation of the averaged perceptron used by <cite>Klementiev et al. (2012)</cite> to evaluate the document representations created by our method. There are different versions of the training set of varying sizes, ranging from 100 to 10,000 documents, and the test sets for both languages contain 5,000 documents. Most related work only reports results using the 1,000 documents sized training set. Following previous work, we tune the hyperparameters of our model on held out documents in the same language that the model was trained on.