# Supplementary data — "A Type Theory of Sense" (draft v0.4.2)

Every text sampled in the paper's experiments, logged verbatim with its full
prompt context, plus all analysis scripts, results, and embeddings. Each
JSONL line is one draw: `{"prompt": ..., "continuation": ...}` (cone runs)
or `{"prefix": ..., "suffix": ..., "infill": ...}` (FIM runs). Indices cited
in the paper's Appendix (log excerpts) are 0-based line numbers in these
files.

## Logs (verbatim, one JSON record per draw)

| File | Experiment | Model | T | n | Feeds |
|---|---|---|---|---|---|
| `continuations_{AMB,FIN,RIV}.jsonl` | pilot 1 (cone, baseline) | GPT-2-small, ancestral sampling | 1.0 | 200 ea. | §6 "GPT-2 null" |
| `p2_continuations_{AMB,FIN,RIV}.jsonl` | pilot 2 (cone, uncalibrated boundary) | gpt-3.5-turbo-instruct | 1.0 | 200 ea. | §6 finding (b): 169/31 imbalance |
| `p3_continuations_{AMB,FIN,RIV}.jsonl` | pilot 3 (cone, calibrated; THE pilot) | gpt-3.5-turbo-instruct | 1.0 | 300 ea. | Fig. pilot, findings (a)-(c); miniature = AMB records #114, #64, #89, #199 |
| `cal_completions_C{1..6}.jsonl` | boundary calibration | gpt-3.5-turbo-instruct | 1.0 | 50 ea. | §6 finding (b) calibration pass¹ |
| `hcal_infills_{NEU,FIN,RIV}.jsonl` | FIM calibration — FAILED instrument | gpt-4o-mini (chat-instructed) | 1.0 | 10 ea. | §6 mode-collapse finding |
| `h_infills_{NEU,FIN,RIV}.jsonl` | 2-horn FIM experiment | gpt-3.5-turbo-instruct (prompted FIM) | 1.0 | 200 ea. | Fig. horn, suffix effect |
| `hn_infills_{NEU,FIN,RIV}.jsonl` | 2-horn, NATIVE FIM (API suffix param) | gpt-3.5-turbo-instruct | 1.0 | 200 ea. | §6 two-instruments finding |
| `nm_pres_{name}.jsonl` (7 names) | name-pilot, presentational readout | gpt-3.5-turbo-instruct | 1.0 | 150 ea. | conclusion, name-pilot outcome |
| `nm_pred_{name}.jsonl` (7 names) | name-pilot, predication readout (5 probes ea.) | gpt-3.5-turbo-instruct | 1.0 | 150 ea. | identity-assent-without-fact-flow finding |
| `nm_flow_*.jsonl` (3 probes) | name-pilot, behavioral flow/segregation | gpt-3.5-turbo-instruct | 1.0 | 20 ea. | transfer 0.90 yes; Hesperus→evening 1.00 |
| `nmcal_*` (2 rounds) | name-pilot calibration (round 1 = referent + epithet confounds, kept) | gpt-3.5-turbo-instruct | 1.0 | 10 ea. | instrument notes |

¹ The calibration originally run before pilot 3 saved counts only
(`calibration-2026-06-10-prelog.json.bak`: C5 = 22 fin / 28 riv). The logged
re-run here (`calibration.json` + `cal_completions_*.jsonl`: C5 = 32/18)
selects the same boundary C5 as most balanced; the swing is n=50 binomial
noise. Both records preserved.

## Prompts / templates

- Cone prompts: the `prompt` field of each record (one per condition).
- FIM template (`run_horn.py::FIM_TEMPLATE`): "Fill in the missing middle of
  the story so it reads as one coherent whole. / STORY BEFORE THE GAP: {p} /
  STORY AFTER THE GAP: {s} / THE MISSING MIDDLE (one or two sentences):"
- gpt-4o-mini instruction (`hcal` runs): see `h_results`/`hcal_results.json`
  `instruction`/`fim_template` fields and `run_horn.py` git history.
- Sense anchors (embedding readout): `run_pilot.py::FIN_ANCHOR/RIV_ANCHOR`.

## Results & embeddings

`results.json` (pilot 1), `p2_results.json`, `p3_results.json`,
`h_results.json`, `hcal_results.json`, `calibration.json` — margins, GMM/BIC,
ε-sweeps, per condition. `*.npz` — raw text-embedding-3-small vectors
(`fs_*` = first-sentence embeddings; `in_*` = infill embeddings; `anchors`).

## Scripts

`run_pilot.py` (pilot 1 + shared estimator code), `run_pilot2.py`,
`run_pilot3.py`, `calibrate.py`, `run_horn.py`, `gen_appendix.py` (builds the
paper's log-excerpts appendix from these files — seed 11235).

## Instrument

Embeddings: OpenAI `text-embedding-3-small`, cosine. π₀ estimator:
single-linkage components at swept ε (`run_pilot.py::pi0_sweep`); 1-D sense
margin = cos(fin anchor) − cos(riv anchor). All runs 2026-06-10 (pilots) per
the paper's draft date.
