Datasets:

jbellis
/

lexonomy

---
license: cc0-1.0
language:
- en
pretty_name: Lexonomy
size_categories:
- 1K<n<10K
tags:
- lexicography
- ontology
- semantics
- taxonomy
- age-of-acquisition
- vocabulary
- lexical-resource
- human-ai-collaboration
---
# Lexonomy

**A hierarchical ontology of English vocabulary in which every placement is an adjudicated argument — and the placement order has been tested against empirical age-of-acquisition norms.**

Lexonomy is a corpus of ~6,000 parent–child–qualifier triples ("slips") organizing English words into a single derivation tree rooted in thirteen primes. Its distinguishing property is not size but **adjudication density**: every edge was individually argued under a written constitution, every mutation carries its own provenance and undo, and the corpus's central structural claim was measured against the Kuperman age-of-acquisition norms (31,105 words).

## The empirical result

The corpus's ordering law — **Temporal Coherence** — holds that a parent concept should not be demonstrably younger than its child: the hierarchy should recapitulate the chronological growth of language. This is a testable claim, and it was tested:

- Every placement was swept against the **Kuperman AoA norms** (Kuperman, Stadthagen-Gonzalez & Brysbaert, 2012; 31,105 words) with a 2.0-year margin.
- The sweep produced **492 corrections**, each individually adjudicated by the human curator with the engine's full argument on record.
- Measured TC debt fell from **808 to 429** suspect placements; the remaining floor is nonzero by design (human-cleared dismissals stay counted as data-suspect forever — the metric gauges the data condition, not the adjudication).

Correction notes survive in the `notes` column, so the reasoning behind each AoA-driven change is inspectable row by row.

## The framework

The generative rule ("Bellis's Law"): every non-prime concept equals a parent word plus a differentiating qualifier —

```
child = parent⟨qualifier⟩
```

The qualifier is a **subtraction, not an addition**: it names what distinguishes this child from its siblings under the same parent. A placement succeeds when the fully qualified breadcrumb from child to prime reads as a stepwise definition.

Thirteen **primes** form the floor (stored with `parent = [prime]`): the five physical senses (*smell, taste, hear, see, touch*); six intellectual prime concepts (*you, thing, here, is, now, do*), corresponding to who/what/where/why/when/how; and *yes, no*. Primes are generated, not carved; everything above them is subsetting.

The framework deliberately **underdetermines the tree**: two competent curators can disagree about a placement. Lexonomy's aim is to make such disagreements atomic and arguable — one edge, one qualifier, one verdict — rather than to claim oracle answers.

## Data structure

One CSV, one row per slip.

| column | meaning |
|---|---|
| `child` | the word being placed |
| `parent` | its parent word, or the sentinel `[prime]` (root by design, 13 rows). A second sentinel, `[orphan]` (placed, parent not yet ruled), is defined by the schema but currently empty — every non-prime row has a parent |
| `qualifier` | the differentiating word (bare canonical value — no bracket notation in the data) |
| `qual_kind` | the qualifier's class: `operator` (ordinary lexical subtraction), `variant` (mechanical/grammatical derivation, e.g. *maker* = *make*⟨noun⟩), `negation` (total subtraction: the child is the parent's direct negation), or empty (unqualified — a standing work item, not a claim) |
| `category` | curator's category tag, where assigned |
| `session_id` | provenance tag for the pass that last ruled the row |
| `notes` | full curation trail: prior placements (`was parent⟨qualifier⟩`), law citations, AoA arguments, recorded dissents (`[alt: …]`). Append-only; loose text by design |
| `status`, `gm_*`, `wl_*` | internal worklist/game flags; safe to ignore for analysis |
| `created_at` | row creation timestamp |

**Notation appearing in the data.** Word values are bare strings with two conventions: square-bracket sentinels occur only in `parent` (`[prime]`, `[orphan]`, documented above), and a parenthesized sense tag disambiguates polysemes in `child`/`parent` — e.g. `scale(weight)` vs. *scale*, `feel(perceive)`, `marked(adjective)` (37 rows). The `notes` column additionally uses the shorthand `parent✖qualifier` to cite placements compactly — `music✖lyrical` means "*music* qualified by *lyrical*"; a `(was parent✖qualifier)` clause records the placement a correction replaced.

Kind census at export: operator 4,326 · variant 1,412 · negation 156 · unqualified 78.

A note on synonymy: rows with qualifier `synonym` (kind `variant`) store a **peer relationship** by database contrivance — the less-common term is filed under the more-common one for storage convenience, but no subordination is claimed. True synonymy proved rare in practice.

## Method: constitutional human–AI curation

The corpus was curated by a single human curator working with an LLM engine under a written constitution — a fixed document of laws (temporal coherence; the least-claiming word upstream; qualifier economy; differential duty within a family; synonym skepticism; no cycles; authorized insertion of missing generations) sent with every engine call. The process:

- The **family** (one parent and all its children), not the slip, is the unit of adjudication — a qualifier's job is defined relative to its siblings.
- Batch passes ran **two independent draws** per family; only consensus committed. Keep-vs-change disagreement resolved to incumbency with the dissent recorded (`[alt: …]` in notes); change-vs-change routed to the human.
- **Certificates, not attendance**: a family counts as done only when every slip was adjudicated; certificates are recorded claims that can be challenged and re-run.
- The human curator is the highest court; the engine drafts and argues, the curator rules.

The full constitution is included in this repository (`CURATION_CONSTITUTION.md`) both as documentation and as a reusable methodology artifact for AI-assisted corpus curation with auditable human authority.

## Intended uses

- **Computational lexical resources**: a small, densely adjudicated complement to WordNet-scale resources; every edge carries its argument.
- **Language acquisition / psycholinguistics**: the TC-vs-AoA sweep is a worked example of testing a hand-built hierarchy against acquisition norms; the corrections are labeled training/evaluation material for placement-ordering models.
- **Lexical semantics**: a corpus of ~6,000 minimal-differentia judgments (which single word distinguishes *fracture* from *crack*?) with recorded alternatives and dissents.
- **Human–AI methodology research**: a complete, documented instance of constitutional LLM curation with provenance.

## Limitations

- **Single curator.** All final rulings are one person's; the constitution and per-row dissent trail are the check, not a second judge. Inter-annotator agreement is an open experiment (the repository owner welcomes it).
- **English only**, and the AoA validation inherits the coverage limits of the Kuperman norms.
- **The core framework is axiomatic.** The prime roster and the qualifier-as-subtraction rule are stipulated, not derived; the empirically tested component is the placement ordering (Temporal Coherence).
- 78 rows are unqualified (placement filed, differentia not yet ruled) — visible work state, not noise. Every non-prime row has a parent (no orphans at publication).

## Links

- Live application: [lexonomy.org](https://lexonomy.org) — the corpus browsable as an interactive tree, with curation worklists.
- Kuperman, V., Stadthagen-Gonzalez, H., & Brysbaert, M. (2012). Age-of-acquisition ratings for 30,000 English words. *Behavior Research Methods*, 44(4), 978–990.

## Citation

```bibtex
@misc{bellis2026lexonomy,
  author = {Bellis, Jack},
  title  = {Lexonomy: a hierarchical vocabulary ontology with age-of-acquisition-validated placement order},
  year   = {2026},
  url    = {https://lexonomy.org}
}
```

## License

CC0 1.0 (public domain dedication) — free to use, share, and adapt for any purpose, no attribution required. Citation is appreciated but not a condition.

	---
	license: cc0-1.0
	language:
	- en
	pretty_name: Lexonomy
	size_categories:
	- 1K<n<10K
	tags:
	- lexicography
	- ontology
	- semantics
	- taxonomy
	- age-of-acquisition
	- vocabulary
	- lexical-resource
	- human-ai-collaboration
	---

	# Lexonomy

	A hierarchical ontology of English vocabulary in which every placement is an adjudicated argument — and the placement order has been tested against empirical age-of-acquisition norms.

	Lexonomy is a corpus of ~6,000 parent–child–qualifier triples ("slips") organizing English words into a single derivation tree rooted in thirteen primes. Its distinguishing property is not size but adjudication density: every edge was individually argued under a written constitution, every mutation carries its own provenance and undo, and the corpus's central structural claim was measured against the Kuperman age-of-acquisition norms (31,105 words).

	## The empirical result

	The corpus's ordering law — Temporal Coherence — holds that a parent concept should not be demonstrably younger than its child: the hierarchy should recapitulate the chronological growth of language. This is a testable claim, and it was tested:

	- Every placement was swept against the Kuperman AoA norms (Kuperman, Stadthagen-Gonzalez & Brysbaert, 2012; 31,105 words) with a 2.0-year margin.
	- The sweep produced 492 corrections, each individually adjudicated by the human curator with the engine's full argument on record.
	- Measured TC debt fell from 808 to 429 suspect placements; the remaining floor is nonzero by design (human-cleared dismissals stay counted as data-suspect forever — the metric gauges the data condition, not the adjudication).

	Correction notes survive in the `notes` column, so the reasoning behind each AoA-driven change is inspectable row by row.

	## The framework

	The generative rule ("Bellis's Law"): every non-prime concept equals a parent word plus a differentiating qualifier —

	```
	child = parent⟨qualifier⟩
	```

	The qualifier is a subtraction, not an addition: it names what distinguishes this child from its siblings under the same parent. A placement succeeds when the fully qualified breadcrumb from child to prime reads as a stepwise definition.

	Thirteen primes form the floor (stored with `parent = [prime]`): the five physical senses (smell, taste, hear, see, touch); six intellectual prime concepts (you, thing, here, is, now, do), corresponding to who/what/where/why/when/how; and yes, no. Primes are generated, not carved; everything above them is subsetting.

	The framework deliberately underdetermines the tree: two competent curators can disagree about a placement. Lexonomy's aim is to make such disagreements atomic and arguable — one edge, one qualifier, one verdict — rather than to claim oracle answers.

	## Data structure

	One CSV, one row per slip.

	\| column \| meaning \|
	\|---\|---\|
	\| `child` \| the word being placed \|
	\| `parent` \| its parent word, or the sentinel `[prime]` (root by design, 13 rows). A second sentinel, `[orphan]` (placed, parent not yet ruled), is defined by the schema but currently empty — every non-prime row has a parent \|
	\| `qualifier` \| the differentiating word (bare canonical value — no bracket notation in the data) \|
	\| `qual_kind` \| the qualifier's class: `operator` (ordinary lexical subtraction), `variant` (mechanical/grammatical derivation, e.g. maker = make⟨noun⟩), `negation` (total subtraction: the child is the parent's direct negation), or empty (unqualified — a standing work item, not a claim) \|
	\| `category` \| curator's category tag, where assigned \|
	\| `session_id` \| provenance tag for the pass that last ruled the row \|
	\| `notes` \| full curation trail: prior placements (`was parent⟨qualifier⟩`), law citations, AoA arguments, recorded dissents (`[alt: …]`). Append-only; loose text by design \|
	\| `status`, `gm_`, `wl_` \| internal worklist/game flags; safe to ignore for analysis \|
	\| `created_at` \| row creation timestamp \|

	Notation appearing in the data. Word values are bare strings with two conventions: square-bracket sentinels occur only in `parent` (`[prime]`, `[orphan]`, documented above), and a parenthesized sense tag disambiguates polysemes in `child`/`parent` — e.g. `scale(weight)` vs. scale, `feel(perceive)`, `marked(adjective)` (37 rows). The `notes` column additionally uses the shorthand `parent✖qualifier` to cite placements compactly — `music✖lyrical` means "music qualified by lyrical"; a `(was parent✖qualifier)` clause records the placement a correction replaced.

	Kind census at export: operator 4,326 · variant 1,412 · negation 156 · unqualified 78.

	A note on synonymy: rows with qualifier `synonym` (kind `variant`) store a peer relationship by database contrivance — the less-common term is filed under the more-common one for storage convenience, but no subordination is claimed. True synonymy proved rare in practice.

	## Method: constitutional human–AI curation

	The corpus was curated by a single human curator working with an LLM engine under a written constitution — a fixed document of laws (temporal coherence; the least-claiming word upstream; qualifier economy; differential duty within a family; synonym skepticism; no cycles; authorized insertion of missing generations) sent with every engine call. The process:

	- The family (one parent and all its children), not the slip, is the unit of adjudication — a qualifier's job is defined relative to its siblings.
	- Batch passes ran two independent draws per family; only consensus committed. Keep-vs-change disagreement resolved to incumbency with the dissent recorded (`[alt: …]` in notes); change-vs-change routed to the human.
	- Certificates, not attendance: a family counts as done only when every slip was adjudicated; certificates are recorded claims that can be challenged and re-run.
	- The human curator is the highest court; the engine drafts and argues, the curator rules.

	The full constitution is included in this repository (`CURATION_CONSTITUTION.md`) both as documentation and as a reusable methodology artifact for AI-assisted corpus curation with auditable human authority.

	## Intended uses

	- Computational lexical resources: a small, densely adjudicated complement to WordNet-scale resources; every edge carries its argument.
	- Language acquisition / psycholinguistics: the TC-vs-AoA sweep is a worked example of testing a hand-built hierarchy against acquisition norms; the corrections are labeled training/evaluation material for placement-ordering models.
	- Lexical semantics: a corpus of ~6,000 minimal-differentia judgments (which single word distinguishes fracture from crack?) with recorded alternatives and dissents.
	- Human–AI methodology research: a complete, documented instance of constitutional LLM curation with provenance.

	## Limitations

	- Single curator. All final rulings are one person's; the constitution and per-row dissent trail are the check, not a second judge. Inter-annotator agreement is an open experiment (the repository owner welcomes it).
	- English only, and the AoA validation inherits the coverage limits of the Kuperman norms.
	- The core framework is axiomatic. The prime roster and the qualifier-as-subtraction rule are stipulated, not derived; the empirically tested component is the placement ordering (Temporal Coherence).
	- 78 rows are unqualified (placement filed, differentia not yet ruled) — visible work state, not noise. Every non-prime row has a parent (no orphans at publication).

	## Links

	- Live application: [lexonomy.org](https://lexonomy.org) — the corpus browsable as an interactive tree, with curation worklists.
	- Kuperman, V., Stadthagen-Gonzalez, H., & Brysbaert, M. (2012). Age-of-acquisition ratings for 30,000 English words. Behavior Research Methods, 44(4), 978–990.

	## Citation

	```bibtex
	@misc{bellis2026lexonomy,
	author = {Bellis, Jack},
	title = {Lexonomy: a hierarchical vocabulary ontology with age-of-acquisition-validated placement order},
	year = {2026},
	url = {https://lexonomy.org}
	}
	```

	## License

	CC0 1.0 (public domain dedication) — free to use, share, and adapt for any purpose, no attribution required. Citation is appreciated but not a condition.