AUTOMATIC ARABIC NAMED ENTITY EXTRACTION AND CLASSIFICATION FOR INFORMATION RETRIEVAL

This article tries to explain our rule-based Arabic Named Entity recognition (NER) and classification
system. It is based on lists of classified proper names (PN) and particularly on syntactico-semantic
patterns resulting in fine classification of Arabic NE. These patterns use syntactico-semantic combination
of morpho-syntactic and syntactic entities. It also uses lexical classification of trigger words and NE
extensions. These linguistic data are essential not only to name entity extraction but also to the taxonomic
classification and to determining the NE frontiers. Our method is also based on the contextualisation and
on the notion of NE class attributes and values. Inspired from X-bar theory and immediate constituents, we
built a rule-based NER system composed of five levels of syntactico-semantic combination. We also show
how the fine NE annotations in our system output (XML database) is exploited in information retrieval and
information extraction.