Methodology
Teanga Bench measures how well a large language model does the work of a language tutor. It has two suites.
- The Blas suite covers Irish, Welsh, Scottish Gaelic, Manx, Breton and Cornish.
- The Tonada suite covers English tutoring for learners whose first language is Portuguese, Spanish, Vietnamese or Japanese.
This page says where the test items come from, how answers are marked, and what the scores can and cannot tell you.
What we publish and what we keep private
The code, the scoring rules, the build scripts and this page are public. For each test, 20 sample items are public. The full item sets are private. They stay on the machine that runs the benchmark and are never put in the repository. We do this so that the test items do not enter model training data.
Failure examples on the model pages come only from the public sample items.
Where the items come from
No answer in the benchmark was written by a language model for the benchmark. A build script copies each answer from a source file, or derives it from a source file by a rule that the script documents. Each item records its source, the licence of the source, and how strong the evidence for its answer is.
The sources are:
- Blas app content. Lesson exercises, noun and verb tables, number tables, prepositional pronouns, gender practice, copula drills and sentences from the Blas language-learning app.
- Tonada app content. English lesson exercises from the Tonada app, with instructions in the learner's first language.
- Parallel corpora. Irish and English legislation from Gaois, Welsh and English text from the Senedd and Welsh legislation, and Breton and French text from Ofis Publik ar Brezhoneg.
- Wikipedia edit history. Real copy-edits to English Wikipedia, used as English error sentences.
- Reference dictionaries. BÚNaMo for Irish, and Kaikki (Wiktionary extracts) for Irish, Scottish Gaelic, Manx and Cornish. These are used to cross-check answers, not to write them.
No human review
No person reviewed the items for this benchmark. Every item has human_checked: false. The app content is itself largely machine-authored and machine-reviewed. A score on an app-derived test therefore measures agreement with the app content. It is not a score against a standard that an expert signed off.
Each item carries an evidence label so that results can be split by it:
| Label | Meaning |
|---|---|
blas-app+bunamo | The answer is in the app content, and every word of it is a form that BÚNaMo lists. |
blas-app+kaikki | The answer is in the app content, and Kaikki lists it as a form. |
blas-app-only | The answer is in the app content. We had no second source. All Welsh and Breton app items are in this group. |
blas-app-unverified | The app content itself marks the sentence as not yet verified. All Cornish sentences in the translation tests are in this group. |
corpus-reference | The reference translation comes from a published parallel corpus. |
distractor-derived-unverified | The error sentence was made by putting a wrong option from an app exercise into the sentence. See "Tutor tests". |
planted-typo | The error is a doubled letter that a script planted in a clean sentence. |
tonada-app-machine-reviewed | The exercise is in the Tonada app content, and the app's automated review marks it verified. |
tonada-app-distractor-machine-reviewed | The error sentence was made by putting a wrong option from a Tonada exercise into the sentence. |
tonada-app-answer-machine-reviewed | A correct sentence from a Tonada exercise, used as a sentence with no error. |
wikipedia-revision-silver-unreviewed | A real edit from the English Wikipedia history. Some are changes of style and not clear errors. |
A cross-check with BÚNaMo or Kaikki shows that a form exists. It does not show that the form is the right one for the question.
Licences
Each item records a licence. The app's own content is marked private-blas or private-tonada. Where the app took a sentence from another source, the item carries the licence of that source:
- Tatoeba sentences: CC BY 2.0 FR.
- Manx sentences from the Gaelg corpus: GPL-3.0.
- Senedd record and Welsh legislation: Open Government Licence v3.0.
- Gaois legislation and Ofis Publik ar Brezhoneg text: CC BY 4.0.
- Wikipedia sentences and Wiktionary text from Kaikki: CC BY-SA 4.0.
- English Wikipedia edit pairs: the text is CC BY-SA 4.0, and the WikiEdits-MultiGEC dataset that collected them is MIT. Both apply.
BÚNaMo, used for cross-checks, is under the Open Database Licence 1.0. Each public sample file has an attribution file beside it that lists its sources, licences and notices.
The tests
The table of tests on this page is generated from the build reports. It shows the number of items, the languages and the evidence counts for each test.
Grammar forms and lesson exercises
The model is asked for one form or one answer: a genitive, a verb form, a prepositional pronoun, a number, the right option in an exercise. The answer is compared with a list of accepted answers after light normalisation (case, apostrophe style and outer spaces do not matter). The list contains every alternative that the source records.
Limit: if a valid dialect or variant form is not in the source, the model is marked wrong for it. Few items have more than one accepted answer, because the sources rarely list alternatives.
Translation and round trip
In the translation test the model translates a sentence into English or from English. In the Breton corpus items the other language is French. The score is chrF++, a standard measure of character and word overlap with the reference translation.
In the round-trip test the model translates a sentence into English, and then, in a new conversation, translates its own English back. The score is chrF++ between the result and the original sentence.
Limits: an overlap measure gives a lower score to a correct translation that uses different words. Most translation items have one reference. Round-trip scores can be high when a model makes the same mistake in both directions.
Tutor tests
The model sees a learner's sentence. The sentence has one error or no error. The model must say if there is an error, give the wrong span, give the correction, give the corrected sentence and explain the error.
The headline score is marked by rule. An item is correct when the model finds the error, fixes it, and changes nothing else. For a sentence with no error, the model must say so and leave the sentence as it is. About one third of the items have no error.
The error sentences are not real learner errors. We found no corpus of real learner errors for these languages. The errors come from three places:
- Exercise distractors. An app exercise gives a sentence with a blank, the right option and wrong options. We put a wrong option in the blank. We keep only grammatical contrasts, such as a missing mutation or a wrong particle. A wrong option is sometimes also valid in the sentence. We do not know how often. A machine reading of 30 random items, not a reading by a speaker, found 2 such items. For 2 of 30, the 95 percent interval is about 1 to 22 percent.
- Planted typos. A script doubles one letter in a clean sentence. Only a few Welsh items use this source.
- Real edits (English only). Real copy-edits from the English Wikipedia edit history.
The Blas tutor test covers Irish, Welsh and Scottish Gaelic only. The app has too few suitable exercises for Manx, Breton and Cornish, and a test built on planted typos alone would mislead.
The explanation score
The explanation is the only part that a model marks. Two judge models from two different model families mark each explanation. The explanation passes only when both judges pass it. The same two judges mark every model, so the scores can be compared. A model from the same family as a judge gets no explanation score.
No person has checked the judges' marks. For this reason the explanation score is reported apart from the headline score, with the rate at which the two judges agreed. If a judge call fails three times, the explanation is left unscored. It is not counted as wrong.
Runs, intervals and cost
- Repeat runs. Each item is run three times with the provider's default settings. An item's score is the mean of its three runs.
- Confidence intervals. Each score has a 95 percent interval from 2,000 bootstrap resamples of the items. When two models' intervals overlap, do not read the difference between them as real.
- Consistency. We report the share of items where the model gave the same result in all three runs.
- Cost. Prices are read from OpenRouter at the start of the run. We report the cost of the run and the cost per correct answer. Each run has a hard cost cap.
- Sampling. Items are selected with a fixed random seed, spread evenly over languages and grammar topics. A rebuild from the same sources gives the same items.
Contamination
A model may have seen some of the source text in training. Each translation item is labelled private or public-source.
- The Irish sentences come from the Blas app's own sentence bank and are private.
- The sentences for the other five languages come from public sources, such as Tatoeba, the Senedd record and dictionary examples. Models may have seen them.
- The parallel corpora are published legal and administrative text.
- The app exercises and tables are not published as data, but the app itself is public.
Known limits
- No human review, as described above.
- The Blas app content has known errors. A build script found one Irish exercise whose marked answer looks wrong. There will be others.
- Cornish text in the sources uses more than one spelling system. A single reference can mark a valid spelling as wrong.
- Manx translation sentences are mostly dictionary examples, and some are archaic.
- Welsh and Breton answers have no second source.
- Scores for small groups, such as one grammar topic in one language, have wide intervals.
Test sets in the Tonada suite
Generated from the build reports in data/build-reports/. Items are sampled with a fixed seed. The full sets are private; 20 items per test are published in samples/tonada.
Items per test, with counts by group. Human-checked counts only items whose source records human review.
| Test | Items | Public | First language | CEFR level | Human-checked |
|---|---|---|---|---|---|
Lesson exercisesexercises | 400 | 20 | Japanese 100, Portuguese 100, Spanish 100, Vietnamese 100 | A1 70, A2 66, B1 128, B2 136 | 0 |
Tutor accuracytutor_accuracy | 360 | 20 | Japanese 90, Portuguese 90, Spanish 90, Vietnamese 90 | A1 56, A2 56, B1 97, B2 107, Unspecified 44 | 0 |
Evidence says how strong the gold answer is: for example whether a course answer is confirmed by a dictionary, or comes from the course alone.
Lesson exercises
Closed English exercises from the Tonada course, with the instruction in the learner's first language, marked against the accepted answers.
- Sources
- grammar-lessons.json, grammar-lessons.review.json, lesson-screens.json, lesson-screens.review.json, tonada-grammar-lessons, tonada-lesson-screens
- Licences
- private-tonada 400
- Evidence
- tonada-app-machine-reviewed 400
- Build report
- tonada_exercises.json
Tutor accuracy
Find and fix the error in an English sentence, or leave a correct sentence alone; an item counts only when the error is found and fixed and nothing else is changed.
- Sources
- eng_sentences_detailed.tsv.bz2, english-clean.jsonl, english-error.jsonl, lesson-screens.json, lesson-screens.review.json, manifest.json, tonada-grammar-lessons, tonada-lesson-screens, wikiedits-multigec-en
- Licences
- CC BY-SA 4.0 (Wikipedia text); MIT (WikiEdits-MultiGEC dataset, https://huggingface.co/datasets/lang-uk/WikiEdits-MultiGEC) 44, private-tonada 316
- Evidence
- tonada-app-answer-machine-reviewed 106, tonada-app-distractor-machine-reviewed 210, wikipedia-revision-silver-unreviewed 44
- Shortfalls
- japanese, portuguese, spanish, vietnamese (see the build report)
- Build report
- tonada_tutor_accuracy.json