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e6bee52 1673e71 554e214 1673e71 554e214 e6bee52 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | # Contributing a model
MILIM-Bench scores any G2P system, including LLMs. Run the model yourself with
whatever tooling you like, then add a column to `data/predictions.tsv`.
Only the words named in each row's `Label` are scored, so the model is given
the sentence plus the words to convert, and returns phonemes for just those.
## 1. Run the model
Use one of the prompts in [PROMPTS.md](PROMPTS.md) as the system prompt. If you
run one unchanged, reuse its id.
You are welcome to write your own instead. Read the existing ones as a
reference, improve on them, and include yours in the PR as a new section with
the next free id. A better prompt is a legitimate contribution, so there is no
need to stick to what is already there.
Your column is named `model@id`, e.g. `gemini-3.1-pro@p1`, so readers can tell
which rows ran the same prompt and are directly comparable. The same model can
appear more than once with different prompts.
Send one row per line, tab-separated: the `Text` from `data/gold.tsv`, then the
target words. Batch around 250 rows per call; the benchmark has 1,653 rows.
```text
תגידי, הכל בסדר איתך? איתך
אני נותן לך את הספר, תקרא אותו. לך
אני נותן לך את הספר, תקראי אותו. לך
שלחתי אליך מכתב, את קיבלת אותו? אליך קיבלת
```
The response is one line per input line, in order, with the phonemes
space-separated:
```text
ʔitˈaχ
leχˈa
lˈaχ
ʔelˈajiχ kibˈalt
```
Check the line count matches what you sent. A dropped line shifts every row
after it; split the batch and retry rather than realigning by hand.
## 2. Write the predictions
Add a column to `data/predictions.tsv` named after your model, same rows in the
same order as `data/gold.tsv`. Each cell pairs the indexes from `Label` with the
phonemes you got back:
```text
3=ʔitˈaχ
2=leχˈa
2=lˈaχ
1=ʔelˈajiχ 4=kibˈalt
```
Normalization is automatic: `x` → `χ`, `r` → `ʁ`, `g` → `ɡ`, and anything
outside the phoneme set is stripped, punctuation included.
## 3. Score
```bash
uv run src/evaluate.py
```
All columns are picked up automatically and reported per category. Open a PR
with the new column.
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