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Automatic Arabic Named Entity Extraction and Classification for Information Retrieval

Authors: Asbayou, Omar;

Automatic Arabic Named Entity Extraction and Classification for Information Retrieval

Abstract

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.

Keywords

fine annotation and classification, Morphosynyaxique analysis, Morphosynyaxique analysis syntactico-semantic patterns rule-based system fine annotation and classification information retrieval information extraction, [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, information retrieval, information extraction, syntactico-semantic patterns, rule-based system, [SHS.LANGUE] Humanities and Social Sciences/Linguistics, [INFO.INFO-IA] Computer Science [cs]/Computer Aided Engineering

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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