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| # 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. | |