For example, disambiguating the identity of the song Down in Figure 1 is easy if we can recognize the nearby string Jay Sean in the context, but the model sometimes fails to do this.
because the CNNs process every example, they may not see enough examples of lexical overlap to pick up on it, and instead try to augment what the word embedding model is already doing with subword information, which ends up being unstable for this task.