Paper Info
Title
RENAR: A Rule-Based Arabic Named Entity Recognition System
Abstract
Named entity recognition has served many natural language processing tasks such as information retrieval, machine translation, and question answering systems. Many researchers have addressed the name identification issue in a variety of languages and recently some research efforts have started to focus on named entity recognition for the Arabic language. We present a working Arabic information extraction (IE) system that is used to analyze large volumes of news texts every day to extract the named entity (NE) types person, organization, location, date, and number, as well as quotations (direct reported speech) by and about people. The named entity recognition (NER) system was not developed for Arabic, but instead a multilingual NER system was adapted to also cover Arabic. The Semitic language Arabic substantially differs from the Indo-European and Finno-Ugric languages currently covered. This article thus describes what Arabic language-specific resources had to be developed and what changes needed to be made to the rule set in order to be applicable to the Arabic language. The achieved evaluation results are generally satisfactory, but could be improved for certain entity types.
Year
DOI
Venue
2012
10.1145/2090176.2090178
ACM Trans. Asian Lang. Inf. Process.
Keywords
DocType
Volume
semitic language,rule-based arabic,entity recognition system,finno-ugric language,entity recognition,natural language processing task,arabic language,arabic information extraction,multilingual ner system,certain entity type,question answering system,arabic language-specific resource,rule based system,machine translation,natural language processing,rule based systems,information retrieval,information extraction,rule based
Journal
11
Issue
Citations 
PageRank 
1
6
0.51
References 
Authors
13
1
Name
Order
Citations
PageRank
Wajdi Zaghouani119721.27