Datasets:

kurdish-tech
/

kurdish-grammar-eval

license: cc-by-sa-4.0
language:
  - kmr
  - ckb
multilinguality: multilingual
task_categories:
  - text-classification
pretty_name: Kurdish Grammar Minimal Pairs (BLiMP-style)
size_categories:
  - n<1K
tags:
  - kurdish
  - kurmanji
  - sorani
  - grammar
  - linguistic-acceptability
  - minimal-pairs
  - evaluation

Kurdish Grammar Minimal Pairs (BLiMP-style) — Kurmancî · Soranî

A grammar-competence benchmark for Kurdish, built on the BLiMP idea: for each item, a correct sentence is paired with a corrupted version where one specific grammar rule has been deliberately broken. Score a language model by checking whether it assigns higher likelihood to the correct sentence than the corrupted one — accuracy well above 50% means the model learned the rule, not just surface fluency.

Built by Kurdish-Tech on KurdishCorpus-clean.

Why this exists

Perplexity tells you a model sounds fluent. It doesn't tell you whether the model actually learned that Kurdish requires an ezafe linker between a noun and its modifier, or that an indefinite marker can't stack, or that a copula has to agree with its subject. This benchmark tests exactly that — a narrower, harder question than fluency. As far as we've found, there is no other published grammar-competence benchmark for Kurdish.

What's covered — and what isn't

Kurmancî and Soranî only. No Zazakî. Every category here required hand-encoding the actual grammar rule (the specific suffixes, the specific whitelist of words that can follow them) — this isn't something that generalizes automatically from one Kurdish variety to another, and we don't have confident, verified knowledge of the equivalent Zazakî rules to encode them correctly. Publishing a guessed Zazakî version would risk teaching people the wrong grammar. We'd rather publish two dialects done honestly than three with one faked. Contributions adding Zazakî are genuinely wanted — open an issue if you have the linguistic background to help.

Category	Type	Rule tested	Kurmancî	Soranî
`ezafe_deletion`	auto-mined	Kurdish noun phrases require an ezafe linker between a head noun and a following possessor/adjective (Kurmancî `-ê/-a/-ên/-yê/-ya/-yên`; Soranî `-ی`). Deleting it is ungrammatical.	300	132
`indefinite_duplication`	auto-mined	Kurmancî `-ek` / Soranî `-êk` mark indefinite singular and cannot stack.	300	270
`copula_agreement`	hand-authored	The copula enclitic must agree with subject person/number (Kurmancî `im/î/e/in`; Soranî `-م/-یت/-ه/-ین/-ن`).	15	15
Total			615	417

Honest limitations — read before quoting a score

This is a pilot-scale heuristic probe, not a peer-reviewed linguistic benchmark:

Scope is narrow on purpose. Three closed-class morphology phenomena, chosen because the rule is unambiguous and mechanically checkable — not a general syntax benchmark.
Auto-mined items are rule-verified, not item-by-item human-checked. Extraction is restricted to a whitelist of common pronouns/adjectives following the candidate suffix specifically to keep precision high, but no native speaker read every one of the 1,002 auto-mined pairs individually.
copula_agreement is small — 15 pairs per dialect. Enough to smoke-test, not enough to trust a score difference between two close models. Treat it as a qualitative check, not a leaderboard metric.
No Zazakî — see above.
Not adversarial. Corruptions are single, clean rule violations, not the harder near-miss distractors a fully adversarial benchmark would use.

Data provenance & license

correct sentences in the auto-mined categories are drawn verbatim from KurdishCorpus-clean's held-out split (never seen by the tokenizer or any model trained on the corpus), from openly-licensed sources only: CC-100 (Common Crawl ToU), HPLT 2.0 (CC0-1.0), and Kurdish Wikipedia (ckbwiki, CC-BY-SA-4.0). The corrupted counterpart is generated by deleting/duplicating the target morpheme in that same sentence. copula_agreement items are original, hand-authored by Kurdish-Tech.

Released under CC BY-SA 4.0.

Format

One JSON object per line, in six files ({dialect}_{category}.jsonl):

{"id": "cc100:ku:379#ez4", "category": "ezafe_deletion", "correct": "Di nava tirkan da dostên me hebin baş e, ...", "corrupted": "Di nava tirkan da dost me hebin baş e, ..."}

Field	Description
`id`	Source document reference for auto-mined items (`gold-{dialect}-copula-N` for hand-authored)
`category`	One of `ezafe_deletion`, `indefinite_duplication`, `copula_agreement`
`correct`	The grammatical sentence
`corrupted`	The same sentence with the target rule violated

Usage

from datasets import load_dataset

ds = load_dataset("kurdish-tech/kurdish-grammar-eval", data_files="kurmanji_ezafe_deletion.jsonl")

# Scoring sketch: accuracy = fraction where the model assigns
# higher likelihood (lower loss) to `correct` than `corrupted`.

Citation

@misc{kurdishtech2026grammareval,
  title  = {Kurdish Grammar Minimal Pairs (BLiMP-style): a pilot grammar-competence benchmark for Kurmanc\^i and Soran\^i},
  author = {{Kurdish-Tech}},
  year   = {2026},
  url    = {https://huggingface.co/datasets/kurdish-tech/kurdish-grammar-eval}
}

Built by Kurdish-Tech — open-source digital infrastructure for the Kurdish language.

Maintained by Alan Hesen.