In this paper, we investigate the use of AL in event extraction.
we apply the active learning approach to the Attack event, because it is the most frequent event type in the ACE corpus, and is particularly challenging because of the large number of different expressions: there are 312 different words in the corpus that serve at least once as the main word (the "trigger") of an Attack event, After studying several sampling strategies, we settled upon a pseudo co-testing approach where a second classifier which solves a coarser variant of the original task is used.