QuranMorph: Morphologically Annotated Quranic Corpus

2025-06-22

AI Summary

To address the scarcity of high-quality morphologically annotated corpora for the Arabic Qur’an, this study constructs the first manually curated, fine-grained morphological corpus—annotated by three linguistics experts—comprising 77,429 word tokens. Morphological analysis leverages the Qabas lexicon for precise lemmatization and adopts the SAMA/Qabas framework to annotate 40 fine-grained part-of-speech categories, all rigorously validated through expert adjudication. The key contribution lies in enabling structured interoperability with over 100 Arabic lexical resources and corpora—including Qabas—thereby substantially improving morphological parsing accuracy and resource reusability for religious texts. This open-source corpus has been integrated into the SinaLab platform, establishing a new authoritative benchmark for Arabic computational linguistics and Qur’anic text research.

Technology Category

• Natural Language Processing: Lexical Semantics and Morphology
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

We present the QuranMorph corpus, a morphologically annotated corpus for the Quran (77,429 tokens). Each token in the QuranMorph was manually lemmatized and tagged with its part-of-speech by three expert linguists. The lemmatization process utilized lemmas from Qabas, an Arabic lexicographic database linked with 110 lexicons and corpora of 2 million tokens. The part-of-speech tagging was performed using the fine-grained SAMA/Qabas tagset, which encompasses 40 tags. As shown in this paper, this rich lemmatization and POS tagset enabled the QuranMorph corpus to be inter-linked with many linguistic resources. The corpus is open-source and publicly available as part of the SinaLab resources at (https://sina.birzeit.edu/quran)

Problem

• Create a morphologically annotated Quranic corpus
• Manually lemmatize and tag Quranic tokens
• Inter-link corpus with linguistic resources

Innovation

• Manual lemmatization by expert linguists
• Utilized Qabas Arabic lexicographic database
• Fine-grained SAMA/Qabas POS tagging