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Text Coherence Scoring/Evidence
Method evidence record

Text Coherence Scoring

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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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Text Coherence Scoring (Local Coherence Modeling)
Taxonomic method record · process-pipeline / text-mining
  • 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. · URL
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Curated claims

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyAutomatic Text Evaluationmachine-suggested · Relational suggestion, not evidence.Same method familyBERT Embeddingsmachine-suggested · Relational suggestion, not evidence.Same method familySentiment Analysismachine-suggested · Relational suggestion, not evidence.Same method familyText Classificationmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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