Before revision:  Then we propose an uncertainty-based active learning strategy called Lowest Token Probability (LTP) which considers not only the final output but also the intermediate results .
After revision:  Then we propose an uncertainty-based active learning strategy called Lowest Token Probability (LTP) which combines the input and output of CRF to select informative instance. LTP is simple and powerful strategy that does not favor long sequences and does not need to invade the model .