Internal and external evidence in the identification and semantic categorization of proper names
Corpus processing for lexical acquisition
Description of a Multilingual Database of Proper Names
PorTAL '02 Proceedings of the Third International Conference on Advances in Natural Language Processing
Using corpus-derived name lists for named entity recognition
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Named Entity recognition without gazetteers
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
The multilingual named entity recognition framework
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
TAGARAB: a fast, accurate Arabic name recognizer using high-precision morphological analysis
Semitic '98 Proceedings of the Workshop on Computational Approaches to Semitic Languages
Recognition and translation of Arabic named entities with NooJ using a new representation model
FSMNLP '11 Proceedings of the 9th International Workshop on Finite State Methods and Natural Language Processing
A hybrid approach to Arabic named entity recognition
Journal of Information Science
Crime profiling for the Arabic language using computational linguistic techniques
Information Processing and Management: an International Journal
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Named entities (NE) occur frequently in Arabic texts, and their recognition is essential. Recognizing and categorizing NE requires both internal (morphological) and external (syntactic) evidences. This paper describes a system that combines a morphological parser and a syntactic parser, that are built with the NooJ linguistic development environment.