bl.addAll(dataset.getStatementsFromStrings(null, "http://swrc.ontoware.org/ontology#employs", instance.toString()));
blackLists.put(instance, bl);
}
// Create a new SVM property predictor
SVMPropertyPredictor pred = new SVMPropertyPredictor();
// Train on the first 100 instances
pred.train(dataset, instances.subList(0, 100), labels.subList(0, 100), blackLists);
// Predict on the rest, note that we also need the blacklists here, since the labels already occur in the test set as well,
// because we do not use an unlabeled test set, which we would use in an application setting.
List<Value> predictions = pred.predict(dataset, instances.subList(100,instances.size()), blackLists);
// Make a sublist of the labels of the test set
List<Value> testLabels = labels.subList(100, labels.size());
// Print out the predictions and compute the accuracy on the test set.