Can someone explain the following comments, for someone with some knowledge of ML but none of NLP? 
&quot;First, it&#x27;s really much better to use Averaged Perceptron, or some other method which can be trained in an error-driven way. You don&#x27;t want to do batch learning. Batch learning makes it difficult to train from negative examples effectively, and this makes a very big difference to accuracy&quot;
I thought that it was typical for suitably regularized batch methods to modestly outperform or at least match (in terms of accuracy) online methods, whose main advantage is their speed.