In this paper, we highlight the learning challenge and show that our learning method, independent of the model architecture, can give a significant gain.
we assume that one of mentions are related to the question and others are false positives because (i) this happens for most cases, as the first example in Table 2, and (ii) even in the case where multiple mentions contribute to the answer, there is often a single span which fits the question the best.