ANERsys 2.0: Conquering the NER task for the Arabic language by combining the Maximum Entropy with POS-tag information

Proceedings of the 3rd Indian International Conference on Artificial Intelligence, IICAI 2007

Volumn , Issue , 2007, Pages 1814-1823

  Benajiba, Yassine ^a   Rosso, Paolo ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ARABIC LANGUAGES; ARABIC TEXTS; COMMERCIAL SYSTEMS; MAXIMUM ENTROPY; NAMED ENTITIES; NAMED ENTITY RECOGNITION; PART-OF-SPEECH TAGGER; SYSTEM ACCURACY;

ARTIFICIAL INTELLIGENCE;

MAXIMUM ENTROPY METHODS;

EID: 84858318906     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

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10. Benajiba, Y., Rosso, P., Benedí Ruíz: ANERsys: An Arabic Named Entity Recognition System Based on Maximum Entropy. In: Proceeding of CICLing-2007, Mexico. Lecture Notes in Computer Science 4394, Springer-Verlag.
11. Diab, M., Hacioglu, K. and Jurafsky, D.: Automatic Tagging of Arabic Text: From raw text to Base Phrase Chunks. In: Proceedings of HLT-NAACL 2004.