It is a merit of this proposal that, in cases like these, it is possible for one to train the generic model of Figure 2 on any large corpus of text, and then use the produced word vectors and compositional weights to initialize the parameters of a more specific version of the architecture.
(2013), for example, compute the conditional probability of observing words in a context around a target word (an approach known as the skip-gram model).