  Discourse relations bind smaller linguistic elements into coherent texts.
However, automatically identifying discourse relations is difficult, because it
requires understanding the semantics of the linked sentences. A more subtle
challenge is that it is not enough to represent the meaning of each sentence of
a discourse relation, because the relation may depend on links between
lower-level elements, such as entity mentions. Our solution computes
distributional meaning representations by composition up the syntactic parse
tree. A key difference from previous work on compositional distributional
semantics is that we also compute representations for entity mentions, using a
novel downward compositional pass. Discourse relations are predicted not only
from the distributional representations of the sentences, but also of their
coreferent entity mentions. The resulting system obtains substantial
improvements over the previous state-of-the-art in predicting implicit
discourse relations in the Penn Discourse Treebank.
