The kernel ability to generate large feature sets is useful to assure we have enough linguistic features to differentiate between the classes, to quickly model new and not well understood linguistic phenomena in learning machines.
it is often possible to manually design features for linear kernels that produce high accuracy and fast computation time whereas the complexity of tree kernels may prevent their application in real scenarios.