--- title: "A Computational Morphology System for Arabic — Al-Shalabi 1998" description: "The paper presents a morphological analyzer for Arabic that recovers the consonantal root and the… 15 references, cited by 7 papers here." authors: ["Riyad Al-Shalabi", "Martha Evens"] year: 1998 venue: "Computational Approaches to Semitic Languages" source: "https://aclanthology.org/W98-1009/" licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)" licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/shalabi-1998-computational-morphology-system-arabic/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shalabi-1998-computational-morphology-system-arabic/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [1998](https://md.research.elamur.ai/free/en/papers/1998/) / A Computational Morphology System for Arabic # A Computational Morphology System for Arabic **Authors:** Riyad Al-Shalabi and [Martha Evens](https://md.research.elamur.ai/free/en/authors/martha-evens/) · **Year:** 1998 · **Venue:** Computational Approaches to Semitic Languages · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/) **Links:** [Publisher's page](https://aclanthology.org/W98-1009/) · [PDF](https://aclanthology.org/W98-1009.pdf) · [OpenAlex](https://openalex.org/W2049992327) **Citations:** 73 citations (OpenAlex, 2026-10-14) · [7](https://md.research.elamur.ai/free/en/papers/shalabi-1998-computational-morphology-system-arabic/cited-by/) in our library, of the 149,439 papers whose bibliographies we read ## Summary The paper presents a morphological analyzer for Arabic that recovers the consonantal root and the pattern of verbs and of nouns and adjectives derived from verbs. It was built to support parsing and information retrieval and is linked to a large Arabic lexicon. The authors judged two-level morphology (PC-KIMMO) a poor fit for root-and-pattern word formation. They first extended the Al-Fedaghi and Al-Anzi pattern-matching method from triliteral to quadriliteral roots. They then replaced it with a faster scheme: - strip the longest possible prefix; - treat the first remaining letter as the first root letter; - test only a handful of letter combinations from the next few characters against a stored root list. The system was tested on 242 conference abstracts of non-vowelized text. It handled every verb-derived word correctly and was roughly eight times faster than the earlier algorithm. A menu interface exposes four functions: full paradigm display, generation of a requested form, grammatical analysis, and root extraction. ## Key points - The evaluation used 242 abstracts drawn from the Saudi Arabian National Computer Conference, totaling 19,167 running words: - 16,775 words had triliteral roots; - 1,124 had quadriliteral roots; - none had quintiliteral roots; - 1,268 were underived ("solid") nouns or foreign borrowings. - All triliteral and quadriliteral cases were analyzed correctly. Colleagues in the Arabic Language Processing Laboratory verified the results. - Average root search per abstract took 2.2 s, versus 17.2 s for the Al-Fedaghi and Al-Anzi algorithm. The new method also used less memory. - The lexicon holds 1,116 regular verb roots plus explicitly stored forms for the 39 most frequent irregular verbs. Arabic script was handled with the Nafitha software. - The four menu options are GetParadigm, GetForm (by mood, person, number, gender), Analyze, and GetRoot. Future work targets vowelized text and generation of derived nouns and adjectives. ## Interesting ideas - Removing the longest prefix pins down the first root letter, so only six letter combinations remain to check against a closed root list. This turns open-ended search into a small, verifiable candidate set. - Patterns are matched by writing placeholder letters into the word at the slot positions and checking whether the result equals the template. This is a simple generate-and-compare test with no learned scoring. - One morphological core serves four different clients: human paradigm browsing, form generation, grammatical analysis for a parser, and root lookup for retrieval. - Rule-based handling covers the regular roots, while the most common irregular verbs are simply listed in full. This splits the problem into a productive part and a memorized exception part. - The evaluation counted words outside the system's scope (underived nouns, borrowings) as a separate category instead of mixing them into errors. ## For Mova How these ideas could serve Mova, our small open language model — its files, stages and tests: - **I1** (tokens): The English lemmatizer could strip the longest known affix and test a short, enumerated list of stem candidates against the lexicon. Each choice would then come with a traceable reason. - **I2** (tokens): Irregular or templated English forms (e.g. ablaut verb classes) could be checked by rendering the template and comparing it to the word. The match itself would serve as the explanation. - **I3** (back): The same inflection tables used by the tagger could drive surface realization in generation. This keeps analysis and generation consistent by construction. - **I4** (tokens): Keeping a small explicit table of high-frequency irregulars beside rule-based morphology avoids distorting the rules with exceptions. - **I5** (learn): Reporting out-of-coverage items as their own bucket in evaluations would make accuracy figures more honest. It would also point directly at gaps to fill. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions - [Illinois Institute of Technology](https://md.research.elamur.ai/free/en/universities/illinois-institute-of-technology/) — University, Chicago, United States · 12 works · 1,006 citations 📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works 🧭 Topics (2): [Semitic languages](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · 2,908 works · [🧩 Morphology](https://md.research.elamur.ai/free/en/topics/morphology/) · 405 works ## Cite Cite as: Riyad Al-Shalabi and Martha Evens. 1998. A Computational Morphology System for Arabic. Computational Approaches to Semitic Languages. The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{alshalabi1998computational, title = {{A Computational Morphology System for Arabic}}, author = {Riyad Al-Shalabi and Martha Evens}, booktitle = {Computational Approaches to Semitic Languages}, year = {1998}, doi = {10.3115/1621753.1621765}, url = {https://doi.org/10.3115/1621753.1621765} } ``` - [← previous DiMLex: A Lexicon of Discourse Markers for Text Generation and Understanding](https://md.research.elamur.ai/free/en/papers/stede-1998-dimlex-lexicon-discourse-markers-text/) - [next → Generating Natural Language Summaries from Multiple On-Line Sources](https://md.research.elamur.ai/free/en/papers/radev-1998-generating-natural-language-summaries-multiple/) - [↑ back to papers of 1998](https://md.research.elamur.ai/free/en/papers/1998/) ## References 15 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. Abu-Arafah, A. 1995. A Grammar for the Arabic Language Suitable for Machine Parsing and Automatic Text Generation. Ph.D. Dissertation, Computer Science Department, Illinois Institute of Technology, Chicago, IL. [find](https://scholar.google.com/scholar?q=Abu%2DArafah%2C+A%2E+1995%2E+A+Grammar+for+the+Arabic+Language+Suitable+for+Machine+Parsing+and+Automatic+Text+Generation%2E+Ph%2ED%2E+Dissertation%2C+Computer+Science+Department%2C+Illinois+Institute+of+Technology%2C+Ch) 2. Abu-Salem, H. 1992. A Microcomputer Based Arabic Bibliographic Information Retrieval System with Relational Thesauri (Arabic ~). h. D i ssertatioa, Computer Science Department, Illinois Institute of Technology, Chicago, IL. [find](https://scholar.google.com/scholar?q=Abu%2DSalem%2C+H%2E+1992%2E+A+Microcomputer+Based+Arabic+Bibliographic+Information+Retrieval+System+with+Relational+Thesauri+%28Arabic+%7E%29%2E+h%2E+D+i+ssertatioa%2C+Computer+Science+Department%2C+Illinois+Institute+of+T) 3. Al-Fedaghi, S. S., and A1-Anzi, F. S. 1989. A New Algorithm to Generate Arabic Root-Pattern Forms, Proceedings of the 1 lth National Computer Conference and Exhibition, March, Dharan, Saudi Arabia, 391-400. [find](https://scholar.google.com/scholar?q=Al%2DFedaghi%2C+S%2E+S%2E%2C+and+A1%2DAnzi%2C+F%2E+S%2E+1989%2E+A+New+Algorithm+to+Generate+Arabic+Root%2DPattern+Forms%2C+Proceedings+of+the+1+lth+National+Computer+Conference+and+Exhibition%2C+March%2C+Dharan%2C+Saudi+Arabia%2C+39) 4. AI-Kharashi, I., and Evens, M. 1994. Comparing Words, Stems, and Roots as Index Terms in an Arabic Information Retrieval System. Journal of the American Society for Information Science. Vol.45, No.8, September 1994, 548-560. [↗](https://doi.org/10.1002/(sici)1097-4571(199409)45:8<548::aid-asi3>3.0.co;2-x) 5. AISamara, K. 1996. An Arabic Lexicon to Support Information Retrieval, Parsing and text Generation. P h . D . Dissertation, Computer Science Department, Illinois Institute of Technology, Chicago, IL. [find](https://scholar.google.com/scholar?q=AISamara%2C+K%2E+1996%2E+An+Arabic+Lexicon+to+Support+Information+Retrieval%2C+Parsing+and+text+Generation%2E+P+h+%2E+D+%2E+Dissertation%2C+Computer+Science+Department%2C+Illinois+Institute+of+Technology%2C+Chicago%2C+IL%2E) 6. Antworth, E., 1992. Glossing Text with the PC-KIMMO Morphological Parser. Computers and the Humanities. Vol-26. [↗](https://doi.org/10.1007/bf00136982) 7. EI-Sadany, T. A., and Hashish, M. A. 1989. An Arabic Morphological System. IBM Systems Journal. Vol.28, No.4, 600-612. [↗](https://doi.org/10.1147/sj.284.0600) 8. Hammouri, A. 1994. An Arabic Lexicon Database to Support Natural Language Processing. Ph.D. Dissertation, Computer Science Department, Illinois Institute of Technology.Chicago, IL. [find](https://scholar.google.com/scholar?q=Hammouri%2C+A%2E+1994%2E+An+Arabic+Lexicon+Database+to+Support+Natural+Language+Processing%2E+Ph%2ED%2E+Dissertation%2C+Computer+Science+Department%2C+Illinois+Institute+of+Technology%2EChicago%2C+IL%2E) 9. Hegazi, N., and EISharkawi, A. A. 1986. Natural Arabic Language Processing, Proceedings of the 9th National Computer Conference and Exhibition, Riyadh, Saudi Arabia, 1-17. [find](https://scholar.google.com/scholar?q=Hegazi%2C+N%2E%2C+and+EISharkawi%2C+A%2E+A%2E+1986%2E+Natural+Arabic+Language+Processing%2C+Proceedings+of+the+9th+National+Computer+Conference+and+Exhibition%2C+Riyadh%2C+Saudi+Arabia%2C+1%2D17%2E) 10. Hmeidi, I. I. 1995. Design and Implementation of Automatic Word and Phrase Indexing for Information Retrieval with Arabic Documents. Ph.D. Dissertation, Computer Science Department, Illinois Institute of Technology, Chicago, IL. [find](https://scholar.google.com/scholar?q=Hmeidi%2C+I%2E+I%2E+1995%2E+Design+and+Implementation+of+Automatic+Word+and+Phrase+Indexing+for+Information+Retrieval+with+Arabic+Documents%2E+Ph%2ED%2E+Dissertation%2C+Computer+Science+Department%2C+Illinois+Institute) 11. Nafitha 1988. User's Guide and Advanced Programmers Reference, release 3.0, Manama, Bahrain: 01 system. [find](https://scholar.google.com/scholar?q=Nafitha+1988%2E+User%27s+Guide+and+Advanced+Programmers+Reference%2C+release+3%2E0%2C+Manama%2C+Bahrain%3A+01+system%2E) 12. Owens, J. 1988. An Introduction to Medieval Arabic Gramatical Theory. The Foundations of Grammar. John Benjamins, Amsterdam. [find](https://scholar.google.com/scholar?q=Owens%2C+J%2E+1988%2E+An+Introduction+to+Medieval+Arabic+Gramatical+Theory%2E+The+Foundations+of+Grammar%2E+John+Benjamins%2C+Amsterdam%2E) 13. Ritchie, G., Black, A., Russell, G., and Pulman, S. 1992. Computational Morphology. MIT Press, Cambridge, MA. [find](https://scholar.google.com/scholar?q=Ritchie%2C+G%2E%2C+Black%2C+A%2E%2C+Russell%2C+G%2E%2C+and+Pulman%2C+S%2E+1992%2E+Computational+Morphology%2E+MIT+Press%2C+Cambridge%2C+MA%2E) 14. Saliba, B., and Al-Dannan, A. 1989. Automatic Morphological Analysis of Arabic: A Study of Content Word Analysis. Proceedings of the First Kuwait Computer Conference, Kuwait, March, 3-5. [find](https://scholar.google.com/scholar?q=Saliba%2C+B%2E%2C+and+Al%2DDannan%2C+A%2E+1989%2E+Automatic+Morphological+Analysis+of+Arabic%3A+A+Study+of+Content+Word+Analysis%2E+Proceedings+of+the+First+Kuwait+Computer+Conference%2C+Kuwait%2C+March%2C+3%2D5%2E) 15. Sproat, R. 1992. Morphology and Computation. MIT press, Cam- bridge, MA. [↗](https://doi.org/10.7551/mitpress/4775.001.0001) *Updated 1 November 2026*