  Chinese discourse coherence modeling remains a challenge taskin Natural
Language Processing field.Existing approaches mostlyfocus on the need for
feature engineering, whichadoptthe sophisticated features to capture the logic
or syntactic or semantic relationships acrosssentences within a text.In this
paper, we present an entity-drivenrecursive deep modelfor the Chinese discourse
coherence evaluation based on current English discourse coherenceneural network
model. Specifically, to overcome the shortage of identifying the entity(nouns)
overlap across sentences in the currentmodel, Our combined modelsuccessfully
investigatesthe entities information into the recursive neural network
freamework.Evaluation results on both sentence ordering and machine translation
coherence rating task show the effectiveness of the proposed model, which
significantly outperforms the existing strong baseline.
