Paper: Automatically Evaluating Text Coherence Using Discourse Relations

ACL ID P11-1100
Title Automatically Evaluating Text Coherence Using Discourse Relations
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

We present a novel model to represent and assess the discourse coherence of text. Our model assumes that coherent text implicitly favors certain types of discourse relation tran- sitions. We implement this model and apply it towards the text ordering ranking task, which aims to discern an original text from a per- muted ordering of its sentences. The experi- mental results demonstrate that our model is able to significantly outperform the state-of- the-art coherence model by Barzilay and Lap- ata (2005), reducing the error rate of the previ- ous approach by an average of 29% over three data sets against human upper bounds. We fur- ther show that our model is synergistic with the previous approach, demonstrating an error reduction of 73% when the features from both models are combined for t...