If we are sufficiently confident about the prediction made by the supervised KPCA model as to the predicted sense for the target word, we need not resort to the semisupervised KPCA method.
to obtain the sense predictions for test instances, we need only transform the corresponding vectors using the trained KPCA model and classify the resultant vectors using nearest neighbors.