We find that our model can capture distant answer-relevant dependencies such as "mean temperature" while the proximity-based baseline model wrongly takes neighboring words of the answer like "coldest" in the generated question.
our  Table 5: Performance for the average relative distance between the answer fragment and other non-stop sentence words that also appear in the ground truth question (BLEU is the average over BLEU-1 to BLEU-4).