| --- |
| license: odc-by |
| language: |
| - ar |
| size_categories: |
| - 100M<n<1B |
| --- |
| |
| # AraMix-Native |
|
|
| A native-Arabic-filtered version of |
| [`AdaMLLab/AraMix`](https://huggingface.co/datasets/AdaMLLab/AraMix) (`minhash_deduped`), |
| derived from [`SultanR/AraMix-Translation-Scores`](https://huggingface.co/datasets/SultanR/AraMix-Translation-Scores): |
| machine-translated and garbled-MT documents removed, **162,887,010 rows kept of |
| 178,883,241 (91.06%)**. All columns preserved. |
|
|
| ## Filter rules |
|
|
| A document is kept iff all of: |
|
|
| 1. `mmbert_translated_score < 0.1`, **or** a *classical-text rescue*: diacritic |
| (tashkeel) ratio ≥ 0.02 over Arabic letters **and** ≥ 3 distinct diacritic |
| classes (fully/partially vocalized classical prose, Qur'anic text, poetry — |
| verified to exclude MT that carries only tanwīn). |
| 2. No China-catalog MT pattern (machinery/manufacturer boilerplate — a large MT |
| class the classifier scores ≈ 0 because it is far more broken than the fluent |
| backtranslations it was trained on). |
| 3. Arabic stopword cadence ≥ 0.035 (orthography-normalized, و/ف proclitics |
| stripped, tatweel removed) — drops keyword-stuffed/garbled pages. |
| 4. ≥ 10 mojibake characters → dropped; < 20 Arabic words → dropped. |
|
|
| | decision | rows | |
| |---|---| |
| | kept (score < 0.1) | 162,281,524 | |
| | kept (classical rescue) | 605,486 | |
| | dropped: translated (score ≥ 0.1) | 2,360,671 | |
| | dropped: catalog MT | 10,087,854 | |
| | dropped: garbled / keyword-stuffed | 2,556,732 | |
| | dropped: too little Arabic | 990,974 | |
|
|
| ## Known residuals (manually verified by sampling) |
|
|
| - Fluent-but-slightly-broken MT that the classifier scores < 0.1 (e.g. pharma |
| pages mixing Latin chemical terms) remains — est. ~1% of kept rows worst-case. |
| - The garble gate wrongly drops a small amount of name-dense prose (sports |
| line-ups, protocol news), est. ≤ 0.5% of the corpus. |
| - The MT classifier (`mmbert_translated_score`, see the scores dataset card) was |
| trained on gemma-4 / Seed-X / Llama-3.1 backtranslations; MT from very |
| different systems (e.g. older SMT) may not be flagged. |
|
|