| --- |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| - translation |
| language: |
| - en |
| - es |
| - de |
| - ja |
| tags: |
| - i18n |
| - localization |
| - translation-quality |
| - llm-as-judge |
| - benchmark |
| pretty_name: UIStringBench |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: public |
| path: data/public.jsonl |
| --- |
| |
| # UIStringBench |
|
|
| **A benchmark for detecting translation errors in software UI strings.** |
|
|
| Machine and LLM translation of locale files fails in ways generic MT benchmarks don't measure: |
| dropped or invented placeholders, collapsed plurals, and — hardest of all — fluent translations |
| that state something the source doesn't (the Spanish that says *"could not be saved"* for |
| *"were saved successfully"*). As of September 2026 there is no standardized public benchmark for |
| this error class. UIStringBench is a first attempt at one. |
|
|
| ## What's in it |
|
|
| Each row is a source/translation pair from the software-UI domain with a gold label: |
|
|
| | field | description | |
| |---|---| |
| | `id` | stable pair id | |
| | `lang` | target language (`es`, `de`, `ja`) | |
| | `source` | English source string | |
| | `translation` | candidate translation | |
| | `label` | `clean` \| `mistranslation` \| `omission` \| `addition` \| `glossary` | |
| | `split` | `public` | |
|
|
| **Public split: 228 pairs** — 168 clean (drawn from real shipped production locale files, including |
| adversarial pairs whose content looks like instructions or JSON), 54 planted errors (18 per |
| category), and 6 glossary violations (deterministically checkable against the included |
| `glossary.json`; no model involved). |
|
|
| **Held-out split: 60 pairs, private.** Kept out of this repository as a contamination defense; |
| leaderboard results report both splits separately. Composition mirrors the public split |
| (42 clean / 6+6+6 planted, no glossary items). |
|
|
| ## Provenance — why you can trust the labels (and how far) |
|
|
| - The public corpus was committed to git (`Shipi18n/shipi18n@60d699b`, 2026-08-16) **before the |
| judge that consumes it was written**, and the evaluation thresholds were fixed before |
| implementation. Pre-registration is the credibility spine of this dataset. |
| - Labels were **not** revised after seeing model results. In published runs, roughly a quarter of |
| the judge's "false positives" turned out to be the judge being right about pairs mislabelled |
| `clean` — they are still counted against the judge, because a corpus you edit after seeing |
| results is not a corpus. |
| - Honest limitations: three language pairs; one domain (UI strings, mostly from one product's |
| site); corpus and held-out split authored by the tool's maintainer with LLM assistance. Planted |
| errors are deliberate and unambiguous — real-world drift is subtler. Treat scores as an |
| engineering QA signal, not a validated academic metric (the GEMBA authors' caution applies |
| here too). |
|
|
| ## Related work |
|
|
| - **GEMBA-MQM** (Kocmi & Federmann, WMT 2023) and successors (RUBRIC-MQM, GEMBA v2): LLM-as-judge |
| MT evaluation on generic sentence pairs. UIStringBench differs in domain (locale files: |
| placeholders, plurals, short ambiguous strings) and in shipping as a runnable dev-tool harness. |
| - **Last Translation Benchmark**: live, crowd-sourced hard-to-translate examples — general MT, |
| not UI strings or structural failure modes. Adjacent, not overlapping. |
| - **COMET/xCOMET**: learned MT metrics on sentence pairs; multi-GB downloads, no locale-file |
| awareness. |
|
|
| ## Running it |
|
|
| The harness lives in the [Shipi18n repo](https://github.com/Shipi18n/shipi18n) under |
| `evals/semantic/`: |
|
|
| ```bash |
| git clone https://github.com/Shipi18n/shipi18n && cd shipi18n |
| JUDGE_MODEL=<your-model> node evals/semantic/run.mjs |
| ``` |
|
|
| The judge design being measured: 3-pass majority vote, MQM-style category output |
| (mistranslation / omission / addition) rather than scalar scores, structural-first filtering. |
| Item-level results are published with each leaderboard release. |
|
|
| ## Versioning |
|
|
| v1 (2026-09). New languages and formats (gettext, ICU plurals) will widen future versions; |
| saturated versions will be re-cut rather than silently edited. Maintainer: the |
| [Shipi18n](https://shipi18n.com) project. Issues and label disputes: |
| [GitHub issues](https://github.com/Shipi18n/shipi18n/issues). |
|
|
