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        <title>Automated Generation of Arabic Verb Conjugations with Multilingual Urdu Translation: An NLP Approach</title>
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    <abstract>This paper presents a rule-based automated system for generating both Arabic verb conjugations and their corresponding Urdu translations. The system processes triliteral, non-weak Arabic roots across key tenses Past Simple, Past Simple Negative, Present Simple, and Present Simple Negative. Addressing the challenges posed by Arabic morphology, our rule-based approach applies patterns and morphological rules to accurately produce verb conjugations, capturing essential grammatical variations in gender, number, and person. Simultaneously, the system generates Urdu translations using predefined patterns that is aligned with the grammatical nuances of Arabic, ensuring semantic consistency. As the first system of its kind, it uniquely provides a cross-lingual resource that bridges two linguistically similar but distinct languages. By focusing on rule based precision and dual-language outputs, it addresses critical gaps in NLP resources, serving as a valuable tool for linguists, educators, and NLP researchers in academic and religious contexts where Arabic and Urdu coexist.</abstract>
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%0 Conference Proceedings
%T Automated Generation of Arabic Verb Conjugations with Multilingual Urdu Translation: An NLP Approach
%A Nawaz, Haq
%A Elobaid, Manal
%A Al-Laith, Ali
%A Ullah, Saif
%Y El-Haj, Mo
%S Proceedings of the 1st Workshop on NLP for Languages Using Arabic Script
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F nawaz-etal-2025-automated
%X This paper presents a rule-based automated system for generating both Arabic verb conjugations and their corresponding Urdu translations. The system processes triliteral, non-weak Arabic roots across key tenses Past Simple, Past Simple Negative, Present Simple, and Present Simple Negative. Addressing the challenges posed by Arabic morphology, our rule-based approach applies patterns and morphological rules to accurately produce verb conjugations, capturing essential grammatical variations in gender, number, and person. Simultaneously, the system generates Urdu translations using predefined patterns that is aligned with the grammatical nuances of Arabic, ensuring semantic consistency. As the first system of its kind, it uniquely provides a cross-lingual resource that bridges two linguistically similar but distinct languages. By focusing on rule based precision and dual-language outputs, it addresses critical gaps in NLP resources, serving as a valuable tool for linguists, educators, and NLP researchers in academic and religious contexts where Arabic and Urdu coexist.
%U https://aclanthology.org/2025.abjadnlp-1.14/
%P 136-143

Markdown (Informal)

[Automated Generation of Arabic Verb Conjugations with Multilingual Urdu Translation: An NLP Approach](https://aclanthology.org/2025.abjadnlp-1.14/) (Nawaz et al., AbjadNLP 2025)

• Automated Generation of Arabic Verb Conjugations with Multilingual Urdu Translation: An NLP Approach (Nawaz et al., AbjadNLP 2025)

ACL

• Haq Nawaz, Manal Elobaid, Ali Al-Laith, and Saif Ullah. 2025. Automated Generation of Arabic Verb Conjugations with Multilingual Urdu Translation: An NLP Approach. In Proceedings of the 1st Workshop on NLP for Languages Using Arabic Script, pages 136–143, Abu Dhabi, UAE. Association for Computational Linguistics.