Understanding scholarly Natural Language Processing system diagrams through application of the Richards-Engelhardt framework

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Authors Guy Clarke Marshall, Caroline Jay, AndrΓ© Freitas arXiv ID 2008.11785 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI, cs.CL Citations 2 Venue arXiv.org Last Checked 4 months ago
Abstract
We utilise Richards-Engelhardt framework as a tool for understanding Natural Language Processing systems diagrams. Through four examples from scholarly proceedings, we find that the application of the framework to this ecological and complex domain is effective for reflecting on these diagrams. We argue for vocabulary to describe multiple-codings, semiotic variability, and inconsistency or misuse of visual encoding principles in diagrams. Further, for application to scholarly Natural Language Processing systems, and perhaps systems diagrams more broadly, we propose the addition of "Grouping by Object" as a new visual encoding principle, and "Emphasising" as a new visual encoding type.
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