ALMA (ألمى)

Arabic Morphology Tagger

Lemmatizer, POS tagger, and root tagger.
Accuracy: POS (93.8%), lemmatization (90.48%), and speed (32K tokens/second). Outperformed all other tools (see article).

  • Download SinaTools (Morph Module), you can also access ALMA memory (morphological solution ordered by frequency) which is part of SinaTools.

    Download Qabas lexicon that we used to build Alma.

  • Lemmatization BenchMarking
    We used two datasets (Arabic Treebank and SALMA) to evaluate four tools in five lemmatization scenarios, keeping the default settings for all tools. For more details, refer to article [1].
    ALMA Benchmarks
    POS BenchMarking
    We used the ATB dataset to evaluate four tools in three POS tagging scenarios, keeping the default settings for all tools. For more details, refer to article [1].
    ALMA POS Benchmarks
    Speed BenchMarking
    We evaluated the lemmatization speed of the four tools (default settings) on the same machine (24 CPU, 47G Memory, CentOS, size 1.3T) using the same setup (reading input from a file and writing output to a file). The experiment was repeated six times, excluding the first run to account for the initial memory loading time of some tools. See article [1] for more details.
    ALMA Benchmarks

  • Mustafa Jarrar, Diyam Akra, Tymaa Hammouda: ALMA: Fast Lemmatizer and POS Tagger for Arabic. In Proceedings of the 2024 AI in Computational Linguistics (ACLING 2024), Procedia Computer Science, Dubai. ELSEVIER.


    Tymaa Hammouda, Mustafa Jarrar, Mohammed Khalilia: SinaTools: Open Source Toolkit for Arabic Natural Language Understanding. In Proceedings of the 2024 AI in Computational Linguistics (ACLING 2024), Procedia Computer Science, Dubai. ELSEVIER.