Like HMMs, PCFGs are generative models, and like them suffer from insufficient sensitivity of local choices to the larger context. CRFs can provide greater context-sensitivity (as in POS tagging and other types of sequence labeling); though they are not directly suited to structure assignment to text, they can be used to learn shallow parsers, which assign phrase types only to nonrecursive phrases (core NPs, PPs, VPs, etc.) (Sha and Pereira 2003).