For bi-LSTM, this is the multi-task learning setup-using MTL improves the results by +0.7 pp (±2.8) on average, but again there is a high variance within the individual scores.
for the other methods, adding the 10,000 randomly selected samples to the training set actually decreases the average accuracy, by −0.4 pp for Norma and −2.0 pp for CRF.