In the case of parsing, weak learners can be seen as weak parsers, trained each on a very small set of templates.
this is not ideal for a parsing model; time efficiency at parse time is important and, depending on the number of weak parsers available, a model selected with this stopping criterion could be huge, and therefore slow at test time.