One might attempt self-training (McClosky et al., 2006), where new instances are generated by applying a trained model to unannotated data, using high-confidence predictions as ground truth labels.
in such a scheme, the expectation is that the unlabelled text already contains errors, which is not usually the case for most freely available text such as Wikipedia articles as they strive towards correctness.