Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice reading comprehension
Table 5: Experimental results of our proposed model on the test set of MCTest.
['Model', 'MC160 Test', 'MC500 Test']
In order to prove our proposed method works well in other languages, we also implement this method on the English corpus called MCTest (richardson2013). In this work, we conduct experiments with the baseline model (Distance Sliding Window) and our proposed method with the Glove word embeddings. As a result, the performances of our proposed model are higher than the baseline model. In particular, the gap between the baseline model and our model are significant with 9.17% on the MC160 test, while the accuracy of the baseline is substantially lower than our model, approximately 3%. These experiments illustrate our proposed method is also effective on other languages.