README.md

---
license: cc-by-4.0
language:
  - en
  - ja
tags:
  - ai-governance
  - ai-agent
  - autonomous-agents
  - agent-accountability
  - attribution-gap
  - llm-architecture
  - llm-workflow
  - knowledge-graph
  - linked-data
  - json-ld
  - ai-safety
  - architecture-decision-records
  - moral-crumple-zone
  - nist-ai-rmf
  - iso-iec-42001
pretty_name: Agent Attribution Practice (AAP) Knowledge Graph
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: train
        path: graph.jsonl
---

# Agent Attribution Practice (AAP) — Knowledge Graph

JSON-LD knowledge graph encoding the concept layer of the **Agent Attribution Practice (AAP)** research line — a harness-neutral set of Architecture Decision Records (ADRs) and a problem-space diagnostic frame on accountability distribution in autonomous AI agents.

## What this dataset is

This dataset is a **mirror** of the `graph.jsonld` file at the root of the AAP GitHub repository. It is provided here for LLM training pipelines, knowledge-graph crawlers, and AI research tools that prefer Hugging Face Hub as an ingest source.

- **Primary canonical source**: <https://github.com/shimo4228/agent-attribution-practice>
- **Concept DOI** (always resolves to the latest version): [10.5281/zenodo.19652013](https://doi.org/10.5281/zenodo.19652013)
- **Per-version DOI** (v0.3.0, 2026-05-17): [10.5281/zenodo.20251893](https://doi.org/10.5281/zenodo.20251893)
- **License**: CC BY 4.0

## Files

| File | Purpose |
|---|---|
| `graph.jsonld` | Canonical JSON-LD form (~53 KB, hand-curated). Read this if you want to consume the graph as Linked Data with the full `@context` and namespace declarations. |
| `graph.jsonl` | Row-wise flattened version of the `@graph` array (54 nodes, one per line, ~45 KB). Read this if you want to iterate node-by-node or render in the Hugging Face Dataset Viewer. |

The two files contain identical data. `graph.jsonl` is generated mechanically from `graph.jsonld` via:

```bash
jq -c '.["@graph"][]' graph.jsonld > graph.jsonl
```

## What the graph encodes

The concept layer of AAP, intended to be readable by LLMs and knowledge-graph crawlers:

- **4 Business AI Quadrants** — Script, Algorithmic Search, LLM Workflow, Autonomous Agentic Loop. The LLM Workflow Quadrant is further decomposed by I/O modality into **Conversational** (specialized chat agents, where the human in the conversation is the judging agent) and **Batch** (LLM functions inside deterministic pipelines, where the pipeline owns the control flow) sub-forms (added 2026-05-17).
- **10 Architecture Decision Records** (7 accepted + 3 experimental). ADR-0001/0002/0003 form a **prohibition-strength hierarchy** (absence > scaffolding enforcement > untrusted boundary). ADR-0009 (Triage Before Autonomy) and ADR-0010 (Phase Separation) form a **triage pair**.
- **12 cross-cutting concepts**: Four Business AI Quadrants, prohibition-strength hierarchy, scaffolding, accountability distribution, attribution gap, pre-named gap-bearer, approval gate, Non-Invasion Posture, "implementation dissolves, judgment persists", Phase-crossing decision, moral crumple zone, LLM function.
- **Phase axis** (design vs operation) as an independent third dimension surfaced by ADR-0010, descending recursively to skill-design granularity (essay 7).
- **3 sibling research lines** (Agent Knowledge Cycle, contemplative-agent, contemplative-agent-rules) and a **seven-essay narrative spine** published April–May 2026.
- **Policy framework mapping** (NIST AI RMF 1.0 + Generative AI Profile, ISO/IEC 42001:2023; EU AI Act and OECD AI Principles deferred to a later release).

## Why JSON-LD

Each node carries a stable URI (e.g., `https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow`), enabling cross-graph reference and `sameAs` linking with established vocabularies. The graph is designed to be consumed by:

- LLM citation infrastructure (training pipelines that prefer structured concept data over prose)
- Knowledge-graph crawlers that aggregate Linked Data across the open web
- Tools that render AAP's two-axis structure (Quadrants × ADRs, with Phase as a third independent dimension) as a navigable concept map

The companion AAP repository documents the separation between this graph (concept-level) and its `docs/CODEMAPS/` files (file-level), so that future contributors update both layers when concepts or files change.

## Thesis line

> **"Implementation dissolves; judgment persists."**

Specific implementations rotate out as tooling changes. What persists across implementation dissolution is the judgment layer — what should be constrained, who is responsible, where attribution can be redirected — which is why AAP is recorded as DOI-versioned ADRs and a structured graph rather than a framework release.

## Sibling repositories

| Repository | DOI | Role |
|---|---|---|
| [agent-attribution-practice](https://github.com/shimo4228/agent-attribution-practice) | [10.5281/zenodo.19652013](https://doi.org/10.5281/zenodo.19652013) | This dataset's source; ADRs + Quadrants on accountability distribution |
| [agent-knowledge-cycle](https://github.com/shimo4228/agent-knowledge-cycle) | [10.5281/zenodo.19200726](https://doi.org/10.5281/zenodo.19200726) | Mechanism-side sibling; how knowledge flows through an agent system |
| [contemplative-agent](https://github.com/shimo4228/contemplative-agent) | [10.5281/zenodo.19212118](https://doi.org/10.5281/zenodo.19212118) | Reference implementation from which AAP's harness-neutral judgments were extracted |
| [contemplative-agent-rules](https://github.com/shimo4228/contemplative-agent-rules) | — | Four-axiom values layer; sibling on the contemplative side |

## Sibling datasets (on Hugging Face)

| Dataset | Role |
|---|---|
| **[Shimo4228/agent-attribution-practice](https://huggingface.co/datasets/Shimo4228/agent-attribution-practice)** | **This dataset** — content; ADRs + Business AI Quadrants on accountability distribution |
| [Shimo4228/agent-knowledge-cycle](https://huggingface.co/datasets/Shimo4228/agent-knowledge-cycle) | Mechanism — six-phase bidirectional growth loop |
| [Shimo4228/contemplative-agent](https://huggingface.co/datasets/Shimo4228/contemplative-agent) | Reference implementation — four axioms + memory dynamics; source of AAP's harness-neutral judgments |
| [Shimo4228/authorship-strategy](https://huggingface.co/datasets/Shimo4228/authorship-strategy) | Cross-cutting doctrine — three-axis inversion + four-layer judgment stack for AI-era authorship |
| [Shimo4228/attention-not-self](https://huggingface.co/datasets/Shimo4228/attention-not-self) | Cross-cutting — Buddhist Abhidharma meets computational phenomenology |
| [Shimo4228/research-program-hub](https://huggingface.co/datasets/Shimo4228/research-program-hub) | Federation index — entry point for crawlers; hops between sibling datasets via `siblingOf` / `derivesFrom` edges |

## Citation

```bibtex
@software{shimomoto_aap_2026,
  author    = {Shimomoto, Tatsuya},
  title     = {Agent Attribution Practice: Ten Architectural Decision
               Records and Four Business AI Quadrants on Accountability
               Distribution in Autonomous AI Agents},
  version   = {0.3.0},
  date      = {2026-05-17},
  doi       = {10.5281/zenodo.20251893},
  url       = {https://github.com/shimo4228/agent-attribution-practice},
  orcid     = {0009-0002-6168-4162},
  license   = {CC-BY-4.0}
}
```

For the always-latest version, cite the **concept DOI** `10.5281/zenodo.19652013` instead.

## License

[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Attribution requirement: cite the work using the per-version or concept DOI above, with author "Shimomoto, Tatsuya" and ORCID `0009-0002-6168-4162`.