Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice reading comprehension
Figure 3: Analysis and visualization of the best model’s result with different groups of the question length.
['Question Length', '#Correct', '#Total', 'Acc.(%)']
To verify whether the length of question was a reason for the poor performance of our best model, we measured the performances of the best model according to the question length. In particular, we divided the development set into five groups corresponding to the following question lengths: ≤10, 10−15, 16−20, 21−25, and ≥26 words. As can be seen from the figure, questions of the 16−20 word length resulted in better performance than questions of other lengths. For short questions, our method predicts less effective. This may be because short questions contain less information beneficial to search for the correct answer. In particular, the performances on shorter questions (64.15% for the ≤10-word questions and 65.18% for 10−15 word questions) are lower than the performances on longer questions which are over 66% in accuracy.