Paper: Extending the Entity-based Coherence Model with Multiple Ranks

ACL ID E12-1032
Title Extending the Entity-based Coherence Model with Multiple Ranks
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

We extend the original entity-based coher- ence model (Barzilay and Lapata, 2008) by learning from more fine-grained coher- ence preferences in training data. We asso- ciate multiple ranks with the set of permuta- tions originating from the same source doc- ument, as opposed to the original pairwise rankings. We also study the effect of the permutations used in training, and the effect of the coreference component used in en- tity extraction. With no additional manual annotations required, our extended model is able to outperform the original model on two tasks: sentence ordering and summary coherence rating.