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Project Charter — Nested Semantic Graph

A Common Representation for Cross-Linguistic Meaning: Computational Architecture for Sub-Graph Matching Search on Ultrametric Semantic Trees

Charter Date: 2026-05-22 Project Lead: Rowan Brad Quni-Gudzinas Program: Ultrametricity Phase: P2 Execution


1. Project Purpose

1.1 Problem Statement

Most global digital infrastructure — search engines, databases, large language models — is built on the structural assumptions of English, an isolating language where words are separate, minimally inflected units. These assumptions systematically fail for polysynthetic languages, where a single word can encode what English requires an entire clause to express. The result is a digital divide: 10-20 million polysynthetic language speakers cannot effectively search, index, or retrieve content in their own languages.

1.2 Proposed Solution

Model meaning as nested ultrametric trees (nested semantic graphs) rather than flat token sequences. In this representation, the English sentence, the Mohawk word-sentence, and the Turkish agglutinative chain all map to the same underlying structure. A search architecture built on sub-graph matching across these trees would be genuinely language-neutral.

1.3 Relationship to Prior Work

This project is a computational implementation sequel to the published conceptual paper "Few Become One: Polysynthetic Communication and the Ultrametric Architecture of Language" (DOI: 10.5281/zenodo.20328374, 2026-05-22). Where "Few Become One" argues that language is an ultrametric tree, this project specifies how to build search, ranking, and matching systems on that tree.


2. Project Scope

2.1 In Scope

Deliverable Description
Internal Literature Review (0.1.md) Comprehensive due diligence across the research corpus
Formal Definitions (0.2.md, 0.2.py) Mathematical grounding with Python verification
Search Architecture Spec (0.3.md) Sub-graph matching, ranking, Q-PNA integration
Cross-Linguistic Examples (0.4.md) English/Turkish/Mohawk isomorphic NSTs
Python Prototype (0.5.py) Parser, matcher, ranking engine
Computational Pathway (0.6.md) Full pipeline architecture and feasibility assessment
Reader Testing & Publication Blind validation and polish for release

2.2 Out of Scope

  • Full-scale production search engine (BACKLOG P3)
  • Training neural semantic parsers (BACKLOG P3)
  • Real corpus validation of Language-Info-Architecture entropy values
  • Native speaker verification of Mohawk/Iroquoian examples
  • Large-scale cross-linguistic corpus collection (BACKLOG P2)

2.3 Explicit Non-Goals

  • This project does NOT argue that language is an ultrametric tree — that argument is in "Few Become One"
  • This project does NOT implement the Q-PNA neural architecture — that specification is published separately
  • This project does NOT provide a production-ready search engine — it provides the architecture specification and prototype

3. Success Criteria

Criterion Measurement
Formal definitions are complete and Python-verified All ultrametric checks pass (0 violations)
Search architecture is fully specified Three-tier matching, ranking algorithm, Q-PNA pipeline documented
Cross-linguistic isomorphism is demonstrated English, Turkish, Mohawk produce identical NSTs
Python prototype executes correctly Parser → tree → matcher → ranking pipeline functional
Reader testing passes No BLOCKING or MAJOR issues remaining
Publication-ready document produced Passes Publication Language Gate (§11.7), has DOI

4. Constraints

Constraint Value
Write sandbox G:\My Drive\projects\nested-semantic-graph\
Branch feature/initial-setup
Python Standard library only (unless documented)
Math formatting LaTeX/MathJax only (§6, Rule 6)
Citations External source files or [LLM-INFERRED] label
Publication User approval required before Obsidian\releases\ move

5. Stakeholders

Stakeholder Role
Rowan Brad Quni-Gudzinas Author, domain expert, approver
Projects Agent Primary executor
REVIEWER Subagent Blind reader testing
QWAV Agent Portfolio-level coordination (informed, not directing)

6. Dependencies

Dependency Type Status
Few Become One (DOI: 10.5281/zenodo.20328374) Conceptual foundation Published
Q-PNA (DOI: 10.5281/zenodo.20287742) Neural architecture Published
Language-Info-Architecture (DOI: 10.5281/zenodo.20137616) Quantitative grounding Published
Tree Cophenetic (DOI: 10.5281/zenodo.20213043) Mathematical formalization Published
ultrametric-ai-poc (GitHub) Reference implementation Published

7. Risks

See RISK-REGISTER.md for complete risk tracking.


8. Approvals

Role Name Date Status
Project Lead Rowan Brad Quni-Gudzinas 2026-05-22 Initiated
Charter Accepted Pending formal acceptance

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