# Build Fast and Accurate Lemmatization for Arabic

arXiv: https://arxiv.org/abs/1710.06700 · HTML: https://mlsanity.com/paper/1710.06700/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Oct 2017.

## Built on by (most cited first, 3 of 3)

- [LAraBench: Benchmarking Arabic AI with Large Language Models](https://mlsanity.com/paper/2305.14982/) (2023)
- [LANS: Large-scale Arabic News Summarization Corpus](https://mlsanity.com/paper/2210.13600/) (2022)
- [Lemmatization as a Classification Task: Results from Arabic across Multiple Genres](https://mlsanity.com/paper/2506.18399/) (2025)

## Abstract (arXiv)

In this paper we describe the complexity of building a lemmatizer for Arabic which has a rich and complex derivational morphology, and we discuss the need for a fast and accurate lammatization to enhance Arabic Information Retrieval (IR) results. We also introduce a new data set that can be used to test lemmatization accuracy, and an efficient lemmatization algorithm that outperforms state-of-the-art Arabic lemmatization in terms of accuracy and speed. We share the data set and the code for public.