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MIZAN

A scalable tool for extracting and classifying Arabic morphological patterns from large text corpora.

MIZAN builds Arabic morphological pattern dictionaries automatically. Given a user-defined morphological template (wazn, وزن — e.g. استفعال, مفعول), it scans an Arabic corpus and identifies every word that matches that template, without relying on any pre-defined lexicon. Matches are aggregated into structured, frequency-annotated dictionaries ready for lexicography, corpus-linguistic research, and Arabic-language education.

  • Author: Almoataz B. Al-Said
  • Affiliation: Kuwait University; Cairo University
  • Year: 2026
  • Distribution: Compiled binary (Windows), academic/research use — see LICENSE

Citation — please cite the peer-reviewed publication

If you use MIZAN, or any results produced by it, in academic work, please cite:

Al-Said, A. B. (2026). Mizan: An Innovative Tool for Building Arabic Morphological Pattern Dictionaries and Enhancing Lexical Resource Development. ACM Transactions on Asian and Low-Resource Language Information Processing, 25(2), Article 11. https://doi.org/10.1145/3786605

System requirements

  • Windows 10/11, 64-bit
  • No Python installation required (the application is fully self-contained)
  • ~200–400 MB free disk space

Download

Download only from the official source: https://github.com/almoatazb/Mizan/releases/latest

Installation

  1. Download MIZAN_v1.0_win64.zip from the release above.
  2. Extract the entire archive to a folder of your choice.
  3. Run mizan.exe from inside the extracted folder.

Known limitations

MIZAN performs template-based pattern matching, not full morphological analysis — it does not verify that a matched word's letters form a genuine triliteral root consistent with the target pattern. Reviewing top-ranked matches is recommended for precision-sensitive research use.

License

Distributed under an academic/research-use license — see the release page for full terms. Redistribution, reverse engineering, and commercial use are not permitted without written permission. Contact: moataz.alsaid@ku.edu.kw

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Morphological Pattern Analyzer for Arabic

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