Process / pipeline
Text Coherence Scoring — Local Coherence Modeling
Text coherence scoring computes a document-level coherence score with machine learning, rooted in the entity-based local coherence model introduced by Barzilay and Lapata (2008). It measures how well the sentences of a text hang together, using either an entity-grid model, a graph-based approach, or a transformer-based model.
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Sources
- Barzilay, R. & Lapata, M. (2008). Modeling Local Coherence: An Entity-Based Approach. Computational Linguistics, 34(1), 1-34. DOI: 10.1162/coli.2008.34.1.1 ↗
- Guinaudeau, C. & Strube, M. (2013). Graph-based Local Coherence Modeling. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL), 93-103. link ↗