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 anal...
Benjamin Farber, Dayne Freitag, Nizar Habash, Owen...
Building an accurate Named Entity Recognition (NER) system for languages with complex morphology is a challenging task. In this paper, we present research that explores the featur...
Yassine Benajiba, Imed Zitouni, Mona T. Diab, Paol...
In this paper we describe an improved version of ANERsys, an Arabic Named Entity Recognition system for open-domain texts. The first version of ANERsys was totally based on the Ma...
Broad-coverage language resources which provide prior linguistic knowledge must improve the accuracy and the performance of NLP applications. We are constructing a broad-coverage ...
We present a diacritization system for written Arabic which is based on a lexical resource. It combines a tagger and a lexeme language model. It improves on the best results repor...