While the contingency counts in Table 2 only hinted a limited benefit of linear-chain features, empirical results show the contraryespecially for order k = 2.
the further increase of k causes overfitting, and skip-chain features seem a better way to capture non-local dependencies while keeping the number of model parameters relatively small.