Determining Case in Arabic: Learning Complex Linguistic Behavior Requires Complex Linguistic Features
Nizar Y. Habash, Ryan Gabbard, Owen Rambow, Seth Kulick, Mitch Marcus · 2007
This paper discusses automatic determination of case in Arabic. This task is a major source of errors in full diacritization of Arabic. We use a gold-standard syntactic tree, and obtain an error rate of about 4.2%, with a machine learning based system outperforming a system using hand-written rules. A careful error analysis suggests that when we account for annotation errors in the gold standard, the error rate drops to 0.8%, with the hand-written rules outperforming the machine learning-based system.