Paper: A Model of Coherence Based on Distributed Sentence Representation

ACL ID D14-1218
Title A Model of Coherence Based on Distributed Sentence Representation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Coherence is what makes a multi-sentence text meaningful, both logically and syn- tactically. To solve the challenge of or- dering a set of sentences into coherent or- der, existing approaches focus mostly on defining and using sophisticated features to capture the cross-sentence argumenta- tion logic and syntactic relationships. But both argumentation semantics and cross- sentence syntax (such as coreference and tense rules) are very hard to formalize. In this paper, we introduce a neural network model for the coherence task based on distributed sentence representation. The proposed approach learns a syntactico- semantic representation for sentences au- tomatically, using either recurrent or re- cursive neural networks. The architecture obviated the need for feature engineering, and learn...