DocumentCode :
3758146
Title :
Improving coverage of rule based NER systems
Author :
Emna Hkiri;Souheyl Mallat;Mounir Zrigui
Author_Institution :
Faculty of sciences of Monastir
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
Named entity recognition (NER) is the problem of identifying (locating and categorizing) atomic entities in a given text that fall into predefined categories or classes. In this work, we developed a bilingual Arabic-English lexicon of named entities (NE) to improve the performance of Arabic rule-based systems. To reach our goal, we followed different steps starting by the pre-editing of the DBpedia linked data entities and the parallel corpus and then applying our automatic model for detection, extraction and translation of Arabic-English Named Entities. Our approach is fully automatic and hybrid, it combines linguistic and statistical methods.
Keywords :
"Organizations","Logic gates","Natural language processing","Training","Data mining","Pragmatics","Text recognition"
Publisher :
ieee
Conference_Titel :
Information & Communication Technology and Accessibility (ICTA), 2015 5th International Conference on
Type :
conf
DOI :
10.1109/ICTA.2015.7426925
Filename :
7426925
Link To Document :
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