إعرب لي i3rbli Beta

Research

Our work stands on published research

i3rbli grew out of academic research on deep learning for Arabic text processing. This page lists research published by our team — and it will keep growing.

Published research

Research published by members of our team during their academic careers, in Arabic natural language processing.

Thesis · Princess Sumaya University for Technology · 2025

Using Deep Learning for Segmentation and Parsing of Arabic Texts: An Integrated Approach

استخدام التعلّم العميق في تجزئة وإعراب النصوص العربية: نهجٌ متكامل

Author: Ibrahim Abed Al-Ghafer — founder of i3rbli

The thesis investigates deep learning techniques for Arabic text processing through an integrated approach that combines two closely related tasks: segmenting Arabic text into its units, and parsing it grammatically (iʿrāb). It is the research foundation behind our work on automated iʿrāb in i3rbli-chat.

This thesis was completed and published as graduate work at Princess Sumaya University for Technology; it is listed here as part of our team's academic background.

Cite

Abed Al-Ghafer, I. (2025). Using deep learning for segmentation and parsing of Arabic texts: An integrated approach [Thesis, Princess Sumaya University for Technology]. ProQuest Dissertations & Theses.

Research interests

The areas where we research, consult, and build.

Arabic NLP Segmentation & morphological analysis iʿrāb & syntactic parsing Deep learning Large language models for Arabic AI in language education

A researcher or organization considering a collaboration?

We welcome research partnerships and co-authored papers.

Email us: [email protected]