This combination provides a framework that benefits from the advantages of both generative and discriminative models.
when there is no or a very small amount of labeled data, a parser could still work by using unsupervised learning approaches to learn the rules, or by simply using a set of hand-built rules (as we did above for the task of semantic tagging).