# A slot head, and the corpus that did not exist this morning

Measured 2026-08-08 on workpc, the same day as `2026-08-08-routing-heads-two-head.md`
and against the same fixtures. Workspace is `~/Programs/embed-training`, new
scripts `slot_grammar.gbnf`, `slot_system.txt`, `label_slots.py`, `merge_slots.py`.

## The corpus was the whole problem

The two-head measurement said BIO slot tags stay in the MASSIVE body, because no
Maven-domain span corpus exists. That was true of found corpora and false of
made ones. Destination had the same shape at breakfast. V-660 gave gemma-4-12b a
string to write and the label problem became a generation problem.

The same trick applies to spans. `slot_grammar.gbnf` emits a list of
`{"slot": ..., "text": ...}` and the enum closes over Maven's own five: `time`,
`text`, `key`, `value`, `fn`. `slot_system.txt` demands each span be an exact
substring of the utterance.

**The agreement filter is free here.** Destination needed a second pass. The
daemon's own router prompt had to route each generated line back. A span needs
no second call. It either occurs in the utterance or it does not, and
`label_slots.py` drops it with `find()`.

1702 rows labelled from `train_v5.jsonl`, the reminder, fact, note, act and
query intents. Chat and system carry no slot and were never asked.

| slot | spans |
|---|---|
| text | 1175 |
| time | 485 |
| fn | 381 |
| key | 72 |
| value | 65 |

37 spans dropped as not-a-substring, 2.2% of the pile. Nothing failed to parse,
which is the grammar doing its job. 409 rows came back with no span at all.
Those are kept and tagged all `O`. An utterance carrying no slot teaches the
head not to invent one. An empty list is a label and not a miss.

`key` and `value` are thin because they come from facts alone. That is the
shape of the corpus, not a labeller failure.

## Three heads on one forward pass

Intent and destination were already two linear heads over one masked mean pool.
Slots is a third head over the per-token states of the same pass, so the marginal
cost is one `Linear(384, 11)`.

The tag set is `O` plus `B-` and `I-` for each of the five. A softmax cannot
emit a tag that does not exist. That is the structural guarantee the GBNF buys
for the teacher, and the head gets it for free.

Two masking rules, both `ignore_index`. A row with no `spans` key contributes
nothing, which covers the 1900 generated destination rows and every chat and
system turn. A padding or special-token position contributes nothing either.

Scoring is exact-match span F1, not token accuracy. Most tokens are `O`, so a
tagger that predicts nothing anywhere scores above 90% on tokens.

## Result

Three seeds, 24 epochs, epoch chosen on the intent dev slice alone.

| | two heads | three heads |
|---|---|---|
| intent mean | 93.6% | 92.8% |
| destination mean | 80.8% | 82.8% |
| destination best | 29/33 (87.9%) | 29/33 (87.9%) |
| slot span F1 mean | — | 72.4% |

**The slot head costs nothing and adds a third decision.** Intent moves 0.8
points down and destination 2 points up. Both sit inside the seed spread those
two numbers already had. Read this as unchanged, not as a trade.

The saved checkpoint is seed 1 at epoch 10: intent 93.2%, destination 81.8%,
slot F1 75.8%. `heads.pt` now carries three state dicts and the `bio` list
beside the intent and source enums.

## Epoch selection is now wrong for one of the three heads

Slot F1 was still climbing when the intent-selected epoch stopped it. Seed 0
selects epoch 13 at 70.9% and reaches 76.1% at epoch 20. Seed 1 selects epoch 10
at 75.8% and reaches 80.0% at epoch 24.

So the three tasks want different epochs and the harness picks one. Two ways
out, and neither was taken here. Select on a joint score, which needs an
argument about weights. Or give the slot head its own dev slice and its own
early stop, which means the heads stop being one checkpoint.

Leaving it costs about 4 points of slot F1 and nothing else. The router
contract is graded on intent. Selecting on it is the conservative choice rather
than an oversight.

## What this does not measure

The same gap as the two-head run. **Nothing of this runs in Go.** Three heads
instead of two does not change that. It does change the export. The slot head
reads the per-token states, so an ONNX graph exposing only the pooled vector is
not enough.

There is no held-out span fixture. Span F1 is measured on the dev slice of the
same distilled corpus, so it scores agreement with gemma rather than
correctness. The V-572 defect utterance, `"напомни в 11:00 позвонить маме"`, is
labelled correctly by the teacher, but one utterance is not a fixture.

`key` at 72 spans and `value` at 65 are too thin to report a per-slot number.
