Overview
An experiment on decomposing language onto initially established graph-theory representation applied then onto some pre-selected transformations (commonly used context/tool related transmutes) (t1,t2,t3) then upon some layers of decomposition finding out the shared context / what we label as a handshake; for the purpose of education / others
Overview source: Curated paper metadata.
Methods and contributions
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Findings and contributions
- Defines graphspeak as an experimental communication method whose medium is permutative graphs requiring a pre-handshake selection of sampling nodes.
- Argues that such a language's success depends not on rigor but on empathy, framed as composing the recipient's capability with their context.
- States planned objectives of testing deployment for kids, for cross-language generalizability, and for rigor.
Methods
- Proposed three-layer graph sampling, conversion and decomposition scheme — Outlines Layer 0-2 steps: sampling nodes with graph theory, converting via chosen permutative formats, then decomposing and comparing similarity.
- Three provisional 'transmute' rules for node composition (Tr1-Tr3) — Defines three temporary notational norms for combining and decomposing nodes, illustrated with car-component examples.
- Planned pipeline of LLM querying with manual human confirmation — Proposes data flows in which LLM labeling of objects and transmutes is followed by a manual confirmation layer before stashing.
- Proposed graph-composition game as a test and application vehicle — Describes a planned game in which players compose trees of 3-node graphs and apply preselected transmutation types.
Summary sources: Paper metadata and evidence · Extracted source text.
PDF downloads
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- graph.pdf PDF · 0.61 MiB · extracted-text source
Citation
Citation metadata follows the unified bibliography.
djuwidja, andrew; Friedman, Daniel. 2025. Graphspeak: of language and handshake. Zenodo. DOI: 10.5281/zenodo.14737156. URL: https://doi.org/10.5281/zenodo.14737156.
Catalog details and resources
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