These represent two extremes of the system: consuming the maximum amount of context, which might give the most robust representation of topic semantics, and consuming the minimum amount of context, which gives the most focused representation of topics semantics (and which more generally might allow the system to directly memorize train-test pairs observed in training).
neither performs as well as the combination of all CNN features, showing that the different granularities capture complementary aspects of the entity linking task.