Finally, we examined the errors of our final adversarially-trained BSAE+SA model on the <cite>AddSent</cite> dataset and found that out of the 21.09% remaining errors (Table 4) , 33.3% (46 cases) of these erroneous predictions occurred within the inserted distractor, and 63.7% (88 cases) occurred on questions that the model got wrong in the original SQuAD dev set (without the inserted distractors).