Paper: Modeling Local Coherence: An Entity-Based Approach

ACL ID P05-1018
Title Modeling Local Coherence: An Entity-Based Approach
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005

This paper considers the problem of auto- matic assessment of local coherence. We present a novel entity-based representa- tion of discourse which is inspired by Cen- tering Theory and can be computed au- tomatically from raw text. We view co- herence assessment as a ranking learning problem and show that the proposed dis- course representation supports the effec- tive learning of a ranking function. Our experiments demonstrate that the induced model achieves significantly higher ac- curacy than a state-of-the-art coherence model.