AL has been successfully applied already for a wide range of NLP tasks, including POS tagging (Engelson and Dagan, 1996), chunking (Ngai and Yarowsky, 2000), statistical parsing (Hwa, 2004), and named entity recognition (Tomanek et al., 2007).
aL is designed in such a way that it selects examples for manual annotation with respect to a single learning algorithm or classifier.