While our MT-based projection approach is unsupervised (i.e., it does not rely on any coreference annotations from the target language), it would be informative to see the performance of the supervised resolvers, since their performance can be viewed as a crude upper bound on the performance of our unsupervised systems.
we train a mention-pair model on the training set using the 23 features shown in Table 1 and SVM light as the underlying learning algorithm 12 , and apply the resulting model in combination with Soon et al.