GGTruth Retrieval Specification v0.1
Abstract GGTruth Retrieval Specification v0.1 defines a low-entropy retrieval grammar for AI-native knowledge systems. It introduces a structured block format for semantic retrieval, provenance-aware parsing, contradiction visibility, canonical phrase reconstruction, and machine-readable corpus construction. The specification is designed for AI ingestion rather than traditional human-first web reading. It proposes stable retrieval blocks with explicit fields such as Q, A, SOURCE, URL, STATUS, CONFIDENCE, SEMANTIC_TAGS, CONTRADICTION_STATE, and CANONICAL_CLUSTER. GGTruth can be applied across domains including games, philosophy, religion, software documentation, historical archives, digital humanities, and AI memory systems. The purpose of the format is to make knowledge easier to retrieve, verify, compare, and reconstruct by AI systems while preserving provenance and uncertainty.
Authors
- Raynor Eissens
Institutions
- Accenture (Switzerland) (CH)
- Ambient Systems (Netherlands) (NL)
Publication Details
- Journal
- Open MIND
- Published
- 2026-05-18
- DOI
- https://doi.org/10.5281/zenodo.20262401
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00