The DAGC-ATS Database for Arabic Grammar Correction for Arabic Summaries

Arabic Grammar Correction is a comprehensive open-domain. Modern methods of correcting Arabic language errors rely on a database specific to a particular field and containing specific words and phrases, which leads to the emergence of the problem of out-of-context words. Due to the growth in recent work for Arabic text summarization and Arabic grammar correction, out-of-context words and the complex nature of Arabic grammar, an open-domain Arabic database is a required resource for Arabic language processing techniques. In this study, A new open-domain Database for Arabic Grammar Correction (DAGC-ATS) is presented to solve the out-of-context words problem, limited domain existing databases for training. The proposed database is based on the description of Arabic grammar using part-of-speech tags and relations between words by a dependency parser. The DAGC-ATS database is based on grammar error detection and correction at the simple sentence level. The database contains entries that describe Arabic grammar rules. The DAGC-ATS database contains two files, one for correcting Arabic simple sentences and the other for correcting incorrect Arabic basic sentences in grammar. It is designed for use only in the training stage. Every entry in the database describes one different grammatical problem, such as gender, number, singular, dual, or plural faults. It contains 9309888 entries. Using the QALB dataset, the system's precision, recall, and F-measure scores were 96.9, 94.80, and 95.83. Additionally, the same system was tested using the EASC database with 785 summaries, and the results for precision, recall, and F-measure were 99.73%, 95.90%, and 97.77%.

@article{Essa2026,
  title     = {The DAGC-ATS Database for Arabic Grammar Correction for Arabic Summaries},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {3},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Nada Essa and Mostafa. M. El-Gayar and Eman M. El-Daydamony},
  doi       = {10.14569/IJACSA.2026.0170369},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170369}
}