---
title: "kg-textgen-order — Mova code model"
description: "Mova code model of kg/src/textgen.rs: components with their labels, obernants and the model text."
url: "https://groupants.elamur.ai/free/en/mova/kg/src/textgen.rs.groupant/order.groupant/"
---
Elamur: [Mova](https://md.mova.elamur.ai/free/en/) · [Dictionary](https://md.dictionary.elamur.ai/free/en/) · [Research](https://md.research.elamur.ai/free/en/) · **Groupants**

This page as HTML: <https://groupants.elamur.ai/free/en/mova/kg/src/textgen.rs.groupant/order.groupant/>

# kg-textgen-order

The groupant beside kg/src/textgen.rs in the Mova repository: what the code computes, what it never does, how to go back from its outputs, its invariants, cost and checks.

## Facts

- **kind:** groupant_fragment
- **status:** partial source bound model
- **source:** [`kg/src/textgen.rs`](https://github.com/ElamurAI/mova-free/blob/main/kg/src/textgen.rs)
- **source SHA-256:** `c3e9c00982be1bbd…`
- **covers:** Bigram observations and subset maximum-score order. (bytes 1107–3709)
- **part of:** [kg-textgen](https://md.groupants.elamur.ai/free/en/mova/kg/src/textgen.rs.groupant/)
- **repository folder:** [`kg/src/textgen.rs.groupant/order.groupant`](https://github.com/ElamurAI/mova-free/tree/main/kg/src/textgen.rs.groupant/order.groupant)
- **repository commit:** `48f2e6f74146`

> **Implementation material.** A Mova code model describes this code at one source revision: partial models, finite checks and their stated scope. It is not a reviewed general exposition, and its labels are shown as written, never raised.

## Components

| component | label | where |
|---|---|---|
| **approximant** | partial | [approximant](#approximant) |
| **ast** | partial | `../syntax.json` |
| **composition** | partial | [composition](#composition) |
| **cost** | partial | [cost](#cost) |
| **descriptant** | present | [descriptant](#descriptant) |
| **invariant** | partial | [invariant](#invariant) |
| **tests** | executed bounded checks | [tests](#tests) |

## Obernants

The typed relations around the forward model: the behaviour complement (what the code never does), the reverse reconstruction (every input compatible with an output) and specialised views.

| id | type | label | where |
|---|---|---|---|
| `behavior_complement` | behavior_complement | partial source derived model | [behavior_complement](#behavior-complement) |
| `reverse_reconstruction` | reverse_reconstruction | partial source derived model | [reverse_reconstruction](#reverse-reconstruction) |
| `class_alias` | class_alias | partial source derived model | [class_alias](#class-alias) |
| `tie_policy` | tie_policy | partial source derived model | [tie_policy](#tie-policy) |
| `smoothing` | smoothing | partial source derived model | [smoothing](#smoothing) |
| `position_tie` | position_tie | partial source derived model | [position_tie](#position-tie) |

## Model text


### descriptant

#### kg-textgen-order

Bigram observations and subset maximum-score order.

##### Modeling epoch — 2026-10-31

Source read before tests and models; retained prospective notes accompany the parent. Current evidence uses bounded invented inputs only. This is partial modeling, not proof or corpus accuracy.

### approximant

#### Forward relation

Observe sorted explicit heads, add start/end transitions. logp=ln((count+.1)/(from+3.2)). DP[mask,last] updates unused next and backpointers, final adds end transition. D[{i},i]=logp(<s>,c_i); for j∉S, D[S∪{j},j]=max_i∈S[D[S,i]+logp(c_i,c_j)]. Final score max_i D[All,i]+logp(c_i,</s>); backpointers recover maximizing permutation.

##### Executable approximant gap

Exact categorical structure, identifiers, parser decisions and effects have no useful percentage metric established here. No executable surrogate, automatic substitution or 1/2/5/10% guarantee is claimed.

### invariant

#### Invariant and domain

For n1..12 and finite counts, recovered order is a head permutation maximizing this recurrence.

##### Cost and resources

O(n^2 2^n) time/O(n2^n) state; each score constructs string keys.

### cost

#### Cost and resources

O(n^2 2^n) time/O(n2^n) state; each score constructs string keys.

### composition

#### Composition

Bigram observations and subset maximum-score order.

Observe sorted explicit heads, add start/end transitions. logp=ln((count+.1)/(from+3.2)). DP[mask,last] updates unused next and backpointers, final adds end transition. D[{i},i]=logp(<s>,c_i); for j∉S, D[S∪{j},j]=max_i∈S[D[S,i]+logp(c_i,c_j)]. Final score max_i D[All,i]+logp(c_i,</s>); backpointers recover maximizing permutation.

The parent invokes scoped transformations through the actual functions named in their source ranges. Children partition useful observations, not a complete semantic proof; boundaries can omit helpers, tests and effects.

### models

### behavior_complement

No transition reuses a selected head. Private n0 is unsafe, and public generate guards it; no unbounded-n contract.

### reverse_reconstruction

Order corresponds to all count tables with same chosen optimum/ties; observations cannot reconstruct sentence histories uniquely.

### class_alias

Prep and quantity details collapse through class before observation; objects retain case.

### tie_policy

Strict > retains first predecessor, last equal final max endpoint selected.

### smoothing

Unseen transition count0 remains finite log probability with alpha.1 and fixed32 classes.

### position_tie

Heads sorted by tuple(word,class); tied coordinates use lexical class, not original member order.


### tests

#### Evidence

Parent source checks (a fragment inherits only the behavior they actually exercise):

- textgen::tests::subject_verb_object
- textgen::wave29::variant_priority_and_head_bounds

Selected kg tests: 15 named outcomes, twice debug/twice release, equal sorted outcomes. Standalone actual global/build.rs: 3 named outcomes per run, twice debug/twice optimized; build_child is normally no-op, parent fixture invokes it against isolated synthetic seeds. Eight compiled source mutations (one per source) each compiled successfully and exited101 on the focused assertion; exact source restoration followed by positive rerun.

This fragment's untested branches remain source-derived. No live graph, DB, corpus, teacher, GPU or held-out evaluation was used. Command specs and numeric exits are retained in the external wave29 graphlang receipt. Strict kg Clippy reports existing source lints; see receipt.