Improving NER in Arabic Using a Morphological Tagger
B. Farber, Dayne Freitag, Nizar Y. Habash, Owen Rambow · 2008
We discuss a named entity recognition system for Arabic, and show how we incorporated the information provided by MADA, a full morphological tagger which uses a morphological analyzer.Surprisingly, the relevant features used are the capitalization of the English gloss chosen by the tagger, and the fact that an analysis is returned (that a word is not OOV to the morphological analyzer).The use of the tagger also improves over a third system which just uses a morphological analyzer, yielding a 14% reduction in error over the baseline.We conduct a thorough error analysis to identify sources of success and failure among the variations, and show that by combining the systems in simple ways we can significantly influence the precision-recall trade-off.