Datasets:
Pakistan Languages Dataset
A parallel dataset of English sentences translated into ~37 languages of Pakistan. One row per English sentence; one column per language, using its ISO 639-3 code.
⚠️ Translation quality varies a lot by language — read this before using the data
Every language column is force-filled: no cell is ever left blank. For high-resource languages this just means a verified translation. For the lowest-resource languages, it can mean best guess at a language it has very little or no training data for — possibly leaning on a related language, a partial/word-by-word construction, or transliteration rather than a fluent, checked translation. Mistakes, awkward phrasing, and outright errors should be expected in those columns.
Two per-row columns tell you exactly which cells to trust less:
low_confidence_languages— comma-separated ISO codes of languages in that row that either never cleared the quality judge (score ≥ 90, or ≥ 80 plus a passing repair pass) or were never attempted by the bulk translation call and had to be force-generated afterward.low_confidence_count— how many of the 37 language columns in that row fall into the above category.coverage_count/filled_languages— the complement: how many, and which, languages in that row are high-confidence (cleared the judge threshold).
Always filter on low_confidence_languages per row rather than trusting the static tier below.
Tier is a general expectation, not a per-row guarantee — an otherwise "high" tier language can
occasionally land in a row's low_confidence_languages if that particular sentence was hard (idioms,
technical jargon, etc.), and a "low" or "experimental" language can occasionally score well.
Language coverage tiers
These tiers describe how reliable each language is expected to be on average, based on how much training data realistically has for it. They are informational only — every language is attempted for every row regardless of tier.
High — genuinely fluent (verify occasional idioms/jargon only)
| Code | Language | Script |
|---|---|---|
| urd | Urdu | Perso-Arabic (Nastaliq) |
| pnb | Punjabi | Perso-Arabic (Shahmukhi) |
| pbu | Pashto | Perso-Arabic |
| snd | Sindhi | Perso-Arabic |
Mid — workable quality, spot-check before trusting fully
| Code | Language | Script |
|---|---|---|
| skr | Saraiki | Perso-Arabic (Shahmukhi) |
| bal | Balochi | Perso-Arabic |
| hno | Hindko | Perso-Arabic |
| phr | Pahari-Pothwari | Perso-Arabic |
| brh | Brahui | Perso-Arabic |
| kas | Kashmiri | Perso-Arabic |
Low — sample-able but inconsistent; spot-check before any real use
| Code | Language | Script |
|---|---|---|
| gju | Gojri | Perso-Arabic |
| scl | Shina | Perso-Arabic |
| khw | Khowar | Perso-Arabic |
| bft | Balti | Perso-Arabic / Tibetan |
| bsk | Burushaski | Perso-Arabic |
| wbl | Wakhi | Perso-Arabic |
| trw | Torwali | Perso-Arabic |
| kls | Kalasha | Latin / Perso-Arabic |
| gwc | Gawri (Kalami) | Perso-Arabic |
| phl | Palula | Perso-Arabic |
Experimental — expect frequent errors; treat as best-effort guesses, not ground truth
Little to no digital text exists for most of these languages anywhere. Translations here are the weakest link in the dataset and are the most likely to be inaccurate, partially transliterated, or borrowed from a related language.
| Code | Language | Script |
|---|---|---|
| dml | Dameli | Perso-Arabic |
| ush | Ushojo | Perso-Arabic |
| ydg | Yidgha | Perso-Arabic |
| dmk | Domaaki | Perso-Arabic |
| btv | Bateri | Perso-Arabic |
| clh | Chilisso | Perso-Arabic |
| gwf | Gowro | Perso-Arabic |
| xka | Kalkoti | Perso-Arabic |
| shd | Kundal Shahi | Perso-Arabic |
| oru | Ormuri | Perso-Arabic |
| wne | Wanetsi (Waneci) | Perso-Arabic |
| mki | Dhatki | Perso-Arabic / Devanagari |
| jdg | Jadgali | Perso-Arabic |
| xhe | Khetrani | Perso-Arabic |
| bdz | Badeshi | Perso-Arabic |
| aeq | Aer | Perso-Arabic |
| haz | Hazaragi | Perso-Arabic |
ISO codes are best-effort — several of these languages have no single agreed-upon code. Verify against Ethnologue/Glottolog before treating a code as authoritative for publication.
Recommended usage
- Training/fine-tuning: filter out rows/cells listed in
low_confidence_languages, or restrict to the High and Mid tiers, unless you specifically want (and can tolerate noise in) Low/Experimental coverage. - Evaluation: do not use Low/Experimental-tier cells as gold references without native-speaker review.
- Research on low-resource MT: the Low/Experimental columns may still be useful as a starting point for further human correction, but should not be presented as verified translations as-is.
Columns
| Column | Description |
|---|---|
english |
Source English sentence |
tier |
Length/complexity tier of the English sentence (not language confidence) |
domain |
Topic/register of the English sentence |
coverage_count |
Number of languages that cleared the quality judge for this row |
filled_languages |
ISO codes of the high-confidence languages for this row |
low_confidence_count |
Number of languages in this row that are best-effort/unverified |
low_confidence_languages |
ISO codes of the best-effort/unverified languages for this row |
<iso_code> (×37) |
Translation text for that language, always non-empty |
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