Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.
Mahany, A., Khaled, H., Ghoniemy, S. (2023). Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.. EKB Journal Management System, 23(1), 29-40. doi: 10.21608/ijicis.2023.176628.1232
Ahmed Mahany; Heba Khaled; Said Ghoniemy. "Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.". EKB Journal Management System, 23, 1, 2023, 29-40. doi: 10.21608/ijicis.2023.176628.1232
Mahany, A., Khaled, H., Ghoniemy, S. (2023). 'Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.', EKB Journal Management System, 23(1), pp. 29-40. doi: 10.21608/ijicis.2023.176628.1232
Mahany, A., Khaled, H., Ghoniemy, S. Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.. EKB Journal Management System, 2023; 23(1): 29-40. doi: 10.21608/ijicis.2023.176628.1232

Arabic Negation and Speculation Scope Detection: a Transformer-based Approach.

International Journal of Intelligent Computing and Information Sciences
Volume 23, Issue 1, March 2023, Page 29-40  XML PDF (521.28 K)
Document Type: Original Article
DOI: 10.21608/ijicis.2023.176628.1232
View on SCiNiTO View on SCiNiTO
Authors
Ahmed Mahany email 1; Heba Khaledorcid 2; Said Ghoniemyorcid 3
1Computer Systems Department, Faculty of Computer and Information Sciences, Ain Shams University
2Department of Computer Systems, Faculty of Computer & Information Sciences, Ain Shams University, Abbasia, Cairo 11566, Egypt
3Prof at Faculty of Computer & Information Sciences, Computer Systems Department, Ain Shams University, Cairo , Egypt.
Abstract
Detecting the negation and speculation linguistic phenomena is vital for the performance of Arabic Natural Language Processing (ANLP) tasks. The negation and speculation scope detection problems have been addressed in a number of studies where most of them focused on the English and Spanish languages. This is due to the lack of corpora annotated for negation and speculation. In this work, the ArNeg corpus, annotated with negation, is extended by annotating it for the speculation to build the ArNegSpec corpus. In addition, we propose a transformer-based learning approach for detecting both the negation and speculation in Arabic texts. The AraBERT models with a Bidirectional Long Short-Term Memory and a Conditional Random Field (BiLSTM-CRF) as a sequence classification layer to achieve this goal. The results reached an F1 measure of 98% for cue identification for both negation and speculation. The proposed approach enhanced the evaluation results of the negation scope detection by 6% in terms of the F1 measure compared to the previous study. Furthermore, it achieved a 95% F1 measure for the speculation scope detection and a PCS value of 96% for both the negation and speculation scope. This approach shows the feasibility of transformer-based learning models in the sequence classification tasks as the detection of the negation and speculation in Arabic.
Keywords
Arabic Language; Negation; Speculation; ArNegSpec; AraBERT
Statistics
Article View: 267
PDF Download: 240