  Discourse relations bind smaller linguistic units into coherent texts.
However, automatically identifying discourse relations is difficult, because it
requires understanding the semantics of the linked arguments. A more subtle
challenge is that it is not enough to represent the meaning of each argument of
a discourse relation, because the relation may depend on links between
lower-level components, 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 from the
distributional representations of the arguments, and 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.
