sawda-bench / README.md
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---
license: cc-by-4.0
language:
- prs
- fa
- en
task_categories:
- translation
pretty_name: "Sawda: Intent-Preserving Translation in Trade Communication (Dari/Farsi–English)"
size_categories:
- n<1K
---
# Sawda
A pilot benchmark for **intent-preserving translation of culturally loaded trade
communication** between Afghan Dari and English. 60 native-validated fictional
items; 324 translations from six open-weights systems; 180 blind human judgments
by a native Dari speaker; two LLM-judge calibration sets.
Paper and code: https://github.com/MurtazaKafka/sawda-bench
## Files
| file | contents |
|---|---|
| `data/items.jsonl` | 60 validated items: `id`, `direction` (fa2en/en2fa), `utterance_src`, `context`, `literal_render`, `intent_render`, `pragmatic_note`, `failure_class`, `tranche` (seed/lit/synth), `lang_code` |
| `data/translations.jsonl` | 324 system outputs (54 eval items × 6 systems), verbatim, with measured token usage; 4 empty outputs flagged |
| `data/human_judgments.jsonl` | 180 blind native-speaker judgments: intent (3/2/1), appropriateness (1–7), notes, quick-flags |
| `data/llm_judgments.jsonl`, `data/llm_judgments_rubric_v1.jsonl` | DeepSeek v4-pro judge calibration (rubric v2 and v1) |
| `data/fable_judgments.jsonl` | Claude Fable 5 panel calibration |
| `data/heldout_ids.json` | 6 items held out as few-shot exemplars (excluded from evaluation) |
| `data/judging_plan.json` | The randomized blind judging order |
| `drafts/*.jsonl` | Pre-validation drafts, released for diffing against validated items |
## Data statement (summary)
- **Language variety**: the Persian side is **Afghan Dari** (all items carry
`lang_code: prs_Arab`); Iranian Farsi appears only as an unwanted output
register in system translations. Direction field names `fa2en`/`en2fa` are
legacy labels denoting Dari.
- **Provenance**: 8 seed items written by a native Dari speaker from lived
trade/family-business communication; 20 items grounded in the taarof and
business-pragmatics literatures; 32 validated synthetic variants. All items
are fictional: no real names, businesses, or identifying details.
- **Annotation**: a single native Dari-speaking validator/judge (the benchmark
author). Judgments are blind to system identity but not item provenance.
No inter-annotator agreement is available yet.
- **Known limitations**: pilot scale (30 judged items); machine judge labels
failed calibration (κ ≤ 0.17) and are released as calibration data only,
not evaluation labels.
## Ethics
Dari materials involve communities under active persecution. All items are
fictional. See the paper's Ethical Considerations section.
## Citation
Paper draft in the GitHub repo (`paper/`). Formal citation forthcoming.