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YallaMorph

YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models

YallaMorph is a large-scale benchmark for evaluating the ability of Large Language Models (LLMs) to perform controlled Arabic morphological generation.

Given an Arabic lemma, part-of-speech (POS), gloss, and a set of target morphosyntactic features, the task is to generate the corresponding fully diacritized Arabic surface form or forms. The benchmark also includes morphologically invalid feature configurations for which no valid form exists.

YallaMorph covers:

  • Verbs
  • Nouns
  • Adjectives
  • Baseword morphology
  • Cliticized forms
  • Morphologically invalid configurations

The benchmark contains 663,804 evaluation instances across 4,795 sampled lemmas.

Repository Structure

YallaMorph/
│
├── sample_data/
│   └── ...
│
├── output_data/
│   └── ...
│
├── prompts/
│   ├── english/
│   │   ├── zero_shot/
│   │   └── few_shot/
│   │
│   └── arabic/
│       ├── zero_shot/
│       └── few_shot/
│
└── README.md

sample_data/

Contains sample instances from the YallaMorph benchmark.

Each benchmark instance specifies a lexical item and the morphological features that the model must realize.

Depending on the POS, these features include:

Verbs

  • Aspect
  • Person
  • Gender
  • Number
  • Voice
  • Mood

Nouns and Adjectives

  • Gender
  • Number
  • Case
  • State

Clitic-aware instances additionally contain positional proclitic and enclitic features.

output_data/

Contains model predictions produced during the YallaMorph experiments.

The experiments evaluate multilingual and Arabic-focused LLMs under different prompting configurations.

Model outputs are generated using a fixed JSON output format and subsequently processed for evaluation.

prompts/

Contains the prompts used to evaluate the models.

Prompts are available in:

  • English
  • Arabic

and under two prompting settings:

  • Zero-shot
  • Few-shot (10-shot)

The prompts are POS-specific, with separate configurations for:

  • Verbs
  • Nouns
  • Adjectives
  • Clitic-aware generation

The few-shot prompts include 10 in-context examples selected from data that is disjoint from the benchmark evaluation instances.

Task

Given an input such as:

Lemma: ...
POS: ...
Gloss: ...

Morphological Features:
...

the model must generate the Arabic form corresponding to the complete morphological specification.

A specification may have:

  1. A single valid Arabic form
  2. Multiple valid Arabic forms
  3. No morphologically valid realization

The expected output format is:

{
  "arabic_forms": ["form1", "form2"],
  "status": "OK"
}

For morphologically impossible configurations:

{
  "arabic_forms": null,
  "status": "IMPOSSIBLE"
}

Benchmark Design

YallaMorph is constructed from the lemma inventory and morphological analyses of CamelMorph MSA, accessed through CAMeL Tools.

The benchmark sampling strategy considers several linguistic and distributional dimensions, including:

  • Lemma frequency
  • Root class
  • Paradigm completeness
  • Stem complexity

The benchmark contains two complementary evaluation subsets:

Baseword : Evaluates core Arabic inflectional morphology.

Cliticization : Evaluates the interaction between inflected forms and Arabic proclitics/enclitics.

Benchmark Statistics

POS Group Baseword Instances Cliticized Instances
Active Perfective Verbs 9,234 45,738
Passive Perfective Verbs 8,964 8,820
Command Verbs 7,794 6,480
Active Imperfective Verbs 39,150 181,800
Passive Imperfective Verbs 39,150 37,800
Nouns 101,898 67,950
Adjectives 32,076 76,950
Total 238,266 425,538

Total benchmark size: 663,804 instances.

Paper

YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models

Mahmoud Reda, Salam Khalifa, Reham Marzouk, and Nizar Habash

Computational Approaches to Modeling Language (CAMeL Lab), New York University Abu Dhabi.

If you use YallaMorph in your research, please cite:

@inproceedings{reda2026yallamorph,
  title     = {YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models},
  author    = {Reda, Mahmoud and Khalifa, Salam and Marzouk, Reham and Habash, Nizar},
  year      = {2026}
}

The final ACL/EMNLP citation information will be updated once the proceedings citation is available.

Acknowledgments

This work was conducted at CAMeL Lab, New York University Abu Dhabi.

We gratefully acknowledge the support and contributions of the CAMeL Lab community and collaborators involved in the development of YallaMorph.

License

License

YallaMorph is released under the following licenses:

  • Benchmark data, sample data, prompts, documentation, and other research artifacts: Creative Commons Attribution 4.0 International (CC BY 4.0).
  • Source code and scripts: MIT License.

YallaMorph is constructed using morphological resources from CamelMorph MSA. Users should also comply with the licenses and attribution requirements of the underlying resources.

Model-generated outputs included in this repository were produced using their respective language models and may additionally be subject to the terms and conditions of the corresponding model providers.

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A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models

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