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        <title>A Rhetorical Citation Graph Model for Characterizing Scientific Findings: Resource Construction and Application to Plant Health</title>
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        <namePart type="given">Anne-Sophie</namePart>
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    <abstract>Understanding how scientific findings are discussed and evaluated over time provides valuable evidence for assessing their reliability. We propose the Rhetorical Citation Graph (RCG), a finding-centric graph model that represents citation events by explicitly linking scientific findings, citing articles, rhetorical functions, and citation contexts. We instantiate this model as the Plant Literature Reliability Network (PLIN), a graph of 262,807 citation events automatically constructed from the plant-health literature using Natural Language Processing methods for citation and finding extraction, and rhetorical stance classification. By integrating provenance data with the rhetorical interpretation expressed in citation contexts, the RCG provides structured evidence for contextual analyses of scientific findings and lays the foundation for longitudinal studies of their evolution, scientific consensus, and reliability. Finally, we illustrate the utility of PLIN through a case study on the curation and enrichment of the EPPO Global Database, a reference knowledge base for plant health.</abstract>
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%0 Conference Proceedings
%T A Rhetorical Citation Graph Model for Characterizing Scientific Findings: Resource Construction and Application to Plant Health
%A Foussat, Anne-Sophie
%A Bossy, Robert
%A Guigue, Vincent
%A Sauvion, Nicolas
%A Nédellec, Claire
%Y Kalo, Jan-Christoph
%Y Nakashole, Ndapa
%Y Razniewski, Simon
%Y Suchanek, Fabian M.
%Y Vlachos, Andreas
%Y McCallum, Andrew
%S Proceedings of the 11th Workshop on Automated Knowledge Base Construction (AKBC 2026)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-464-4
%F foussat-etal-2026-rhetorical
%X Understanding how scientific findings are discussed and evaluated over time provides valuable evidence for assessing their reliability. We propose the Rhetorical Citation Graph (RCG), a finding-centric graph model that represents citation events by explicitly linking scientific findings, citing articles, rhetorical functions, and citation contexts. We instantiate this model as the Plant Literature Reliability Network (PLIN), a graph of 262,807 citation events automatically constructed from the plant-health literature using Natural Language Processing methods for citation and finding extraction, and rhetorical stance classification. By integrating provenance data with the rhetorical interpretation expressed in citation contexts, the RCG provides structured evidence for contextual analyses of scientific findings and lays the foundation for longitudinal studies of their evolution, scientific consensus, and reliability. Finally, we illustrate the utility of PLIN through a case study on the curation and enrichment of the EPPO Global Database, a reference knowledge base for plant health.
%U https://aclanthology.org/2026.akbc-1.18/
%P 247-260

Markdown (Informal)

[A Rhetorical Citation Graph Model for Characterizing Scientific Findings: Resource Construction and Application to Plant Health](https://aclanthology.org/2026.akbc-1.18/) (Foussat et al., AKBC 2026)

• A Rhetorical Citation Graph Model for Characterizing Scientific Findings: Resource Construction and Application to Plant Health (Foussat et al., AKBC 2026)

ACL

• Anne-Sophie Foussat, Robert Bossy, Vincent Guigue, Nicolas Sauvion, and Claire Nédellec. 2026. A Rhetorical Citation Graph Model for Characterizing Scientific Findings: Resource Construction and Application to Plant Health. In Proceedings of the 11th Workshop on Automated Knowledge Base Construction (AKBC 2026), pages 247–260, Budapest, Hungary. Association for Computational Linguistics.