On the one hand, while syntactic information (i.e., the dependency tree) can directly connect "will" to "go", it will also promote some noisy words (i.e., "back") at the same time due to the direct links (see the dependency tree in Figure 1).
while deep learning models with the sequential structure can help to downgrade the noisy words (i.e., "back") based on the semantic importance and the close distance with "go", these models will struggle to capture "will" for the factuality of "go" due to their long distance.