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taqbaylit/kabyle-verbs

Kabyle Verbs — Kabyle Verb Conjugation Kabyle verb conjugation dataset — 6,198 verbs, ~344,000 conjugated forms, covering aorist, preterite, imperative, participles, and intensive forms. Data source: amyag.com, work by Kamal Nait Zerrad. Summary Property Value Language Kabyle (taqbaylit) Verbs 6,198 Total conjugated forms 344,745 Unique forms 214,276 Grammatical tenses 11 (aorist, preterite, negative preterite, imperative, intensive aorist… See the full description on the dataset page: https://huggingface.co/datasets/taqbaylit/kabyle-verbs.

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Kabyle Verbs — Kabyle Verb Conjugation

Kabyle verb conjugation dataset — 6,198 verbs, ~344,000 conjugated forms, covering aorist, preterite, imperative, participles, and intensive forms.

Data source: amyag.com, work by Kamal Nait Zerrad.


Summary

PropertyValue
LanguageKabyle (taqbaylit)
Verbs6,198
Total conjugated forms344,745
Unique forms214,276
Grammatical tenses11 (aorist, preterite, negative preterite, imperative, intensive aorist, intensive imperative, participles...)
Persons1s, 2s, 3s m, 3s f, 1p, 2p m, 2p f, 3p m, 3p f + participle
FormatStructured JSON / HuggingFace Datasets
LicenseCC-BY-SA 4.0

Repository Structure

This repository contains 3 configurations:

1. conjugation-tables — Raw Tables

Raw dataset with complete conjugation tables for each verb.

python
from datasets import load_dataset
ds = load_dataset("boffire/kabyle-verbs", "conjugation-tables")

Fields:

  • id — unique verb identifier
  • name — infinitive (e.g., yeɣra, addi)
  • translation — French translation
  • hasDirectionalParticle — directional particle present
  • isIrregular — irregular verb
  • isDerived — derived verb
  • imperative, aorist, preterite, negativePreterite — forms by person (JSON)
  • aoristParticiple, preteriteParticiple, negativePreteriteParticiple — participles
  • intensiveForms — intensive forms with their own tenses
  • pattern — morphological pattern (id, model verb, number)

2. seq2seq — Pairs for Automatic Conjugator

(input, target) format for training a seq2seq model (T5, mT5, etc.) to conjugate.

python
ds = load_dataset("boffire/kabyle-verbs", "seq2seq")

Example format:

input  : "yeɣra | aorist | 1s"
target : "ɣraɣ"

input  : "addi | imperative | 2s"
target : "addi"

input  : "addi | preterite participle | participle"
target : "yuddin"

Splits:

  • train: 310,270 examples
  • validation: 17,237 examples
  • test: 17,238 examples

3. lemmatizer — Pairs for Lemmatization

Inverse format: (form, context) for training a lemmatizer / morphological analyzer.

python
ds = load_dataset("boffire/kabyle-verbs", "lemmatizer")

Example format:

form   : "ɣraɣ"
target : "yeɣra | aorist | 1s"

Splits:

  • train: 310,270 examples
  • validation: 17,237 examples
  • test: 17,238 examples

Tense Distribution

TenseNumber of forms
Intensive aorist76,004
Preterite60,183
Negative preterite60,150
Aorist59,156
Intensive imperative23,134
Imperative18,245
Intensive aorist participle14,374
Preterite participle9,854
Aorist participle9,849
Negative intensive aorist participle7,720
Negative preterite participle6,076

Use Cases

Automatic Conjugator

Train a T5/mT5 model to generate the conjugated form from the verb, tense, and person.

python
from transformers import T5Tokenizer, T5ForConditionalGeneration

tokenizer = T5Tokenizer.from_pretrained("google/mt5-small")
model = T5ForConditionalGeneration.from_pretrained("google/mt5-small")

# Fine-tune on the seq2seq dataset

Lemmatizer / Morphological Analyzer

Train a model to recover the infinitive, tense, and person from an inflected form.

Orthographic Correction

Use reference forms to automatically correct conjugation errors in Kabyle text.

MT/ASR Corpus Enrichment

Generate paraphrases by varying verb tenses in parallel corpora (Tatoeba, Common Voice, etc.).

Linguistic Resource

Reference for linguists, Kabyle learners, and language learning tools.


Notes on Overlapping Forms

Approximately 22.7% of forms appear in multiple contexts. This is expected because the dataset lists conjugation tables for both the preterite and the negative preterite, and Kabyle forms the negative using preverbal particles (ur... ara) rather than by altering the verb stem. Consequently, the verb form itself remains identical across these two tenses. Some participle forms also overlap with finite forms. This is not a defect in the data, but a reflection of the Kabyle morphological system.

For the conjugator (forward task), this is not a problem: the model generates the correct form given the explicit tense and person. For the lemmatizer (inverse task), a contextual model is needed, or ambiguity must be accepted.


Related Resources


Citation

If you use this dataset, please cite:

bibtex
@dataset{kabyle-verbs-2026,
  author = {MOKRAOUI, Athmane},
  title = {Kabyle Verbs: Kabyle Verb Conjugation},
  year = {2026},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datasets/boffire/kabyle-verbs}
}

Contact

  • Author: Athmane MOKRAOUI (boffire)
  • HF Profile: https://huggingface.co/boffire
  • Language: Kabyle (taqbaylit) — Amazigh language spoken in Algeria
  • Data source: amyag.com, work by Kamal Nait Zerrad