PROCESSING TOOLS FOR CORPUS LINGUISTICS: A CASE STUDY ON ARABIC HISTORICAL CORPUS

Abstract

This paper explores the development, design, and reconstruction of a Historical Arabic Corpus (HAC), which covers more than 1600 years of uninterrupted language use. The study emphasizes the technical aspects followed to enhance the system and provide a usable concordancer, along with simple experiments conducted on the corpus and the concordancer. Arabic has a rich literary and cultural heritage spanning thousands of years. The inclusion of digital resources and the advancement in natural language processing (NLP) technology have made Arabic historical corpora increasingly crucial for researchers and learners worldwide. By integrating HAC and its tools into Arabic language learning, learners can delve deeper into vocabulary and culture and gain valuable insights that improve their language skills and understanding of Arabic. This combination of human guidance and NLP technology makes learning an engaging and enjoyable experience, offering a dynamic and authentic way to master the Arabic language. [JJCIT 2024; 10(4.000): 393-411]

Keywords

• historical arabic corpus
• corpus tools
• concordance
• learning arabic
• data normalization
• semantic shifting