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Speech & natural language publications January 1, 2008

Improving NER in Arabic using a morphological tagger

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Farber B., Freitag D., Habash N., Rambow O. Improving NER in Arabic using a morphological tagger, in Proceedings of LREC 08, 2008.

Abstract

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.

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