For future work, we suspect that a more thorough exploration of input representations could yield better results. Experiment 11 implies that there could be a trade-off between model performance and ability for active learning to work depending on which input representation is being utilized. Thus, finding a better input representation could yield success in active learning. We also propose exploring the more global methods for active learning, such as expected model change, which were not explored in this work.