First, except for the largest minibatch size of 48, minibatch learning generally improves the accuracy  of the converged model, which is explained by our intuition that optimization with a larger constraint set could improve the margin.
online learning for NLP typically involves expensive inference on each example for 10 or more passes over millions of examples, which often makes training too slow in practice; for example systems such as the popular (2nd-order) MST parser (McDonald and Pereira, 2006) usually require the order of days to train on the Treebank on a commodity machine (McDonald et al., 2010).