---
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](https://github.com/alexwarstadt/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](https://github.com/Kurdish-Tech) on
[KurdishCorpus-clean](https://huggingface.co/datasets/kurdish-tech/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](https://github.com/Kurdish-Tech)** —
open an issue if you have the linguistic background to help.

## Categories

| 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](https://huggingface.co/datasets/kurdish-tech/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`):

```json
{"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

```python
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

```bibtex
@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](https://github.com/Kurdish-Tech) — open-source digital
infrastructure for the Kurdish language.*

Maintained by Alan Hesen.