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This paper considers the problem of automatic assessment of local coherence. We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. We view coherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. Our experiments demonstrate that the induced model achieves significantly higher accuracy than a state-of-the-art coherence model. . | Modeling Local Coherence An Entity-based Approach Regina Barzilay Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology regina@csail.mit.edu Mirella Lapata School of Informatics University of Edinburgh mlap@inf.ed.ac.uk Abstract This paper considers the problem of automatic assessment of local coherence. We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. We view coherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. Our experiments demonstrate that the induced model achieves significantly higher accuracy than a state-of-the-art coherence model. 1 Introduction A key requirement for any system that produces text is the coherence of its output. Not surprisingly a variety of coherence theories have been developed over the years e.g. Mann and Thomson 1988 Grosz et al. 1995 and their principles have found application in many symbolic text generation systems e.g. Scott and de Souza 1990 Kibble and Power 2004 . The ability of these systems to generate high quality text almost indistinguishable from human writing makes the incorporation of coherence theories in robust large-scale systems particularly appealing. The task is however challenging considering that most previous efforts have relied on handcrafted rules valid only for limited domains with no guarantee of scalability or portability Reiter and Dale 2000 . Furthermore coherence constraints are often embedded in complex representations e.g. Asher and Lascarides 2003 which are hard to implement in a robust application. This paper focuses on local coherence which captures text relatedness at the level of sentence-to- sentence transitions and is essential for generating globally coherent text. The key premise of our work is that the distribution of entities in locally coherent texts .
