It is difficult for rule-based methods or even statistical featurebased methods to capture the full range of NL contexts which map to a semantic concept because they tend to enumerate these contexts.
kernel methods allow a convenient mechanism to implicitly work with a potentially infinite number of features which can robustly capture these range of contexts even when the data is noisy.