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Persian Named Entity Recognition based with Local Filters
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 100 - Number 4
Year of Publication: 2014
|
10.5120/17510-8062 |
Morteza Kolali Khormuji and Mehrnoosh Bazrafkan. Article: Persian Named Entity Recognition based with Local Filters. International Journal of Computer Applications 100(4):1-6, August 2014. Full text available. BibTeX
@article{key:article,
author = {Morteza Kolali Khormuji and Mehrnoosh Bazrafkan},
title = {Article: Persian Named Entity Recognition based with Local Filters},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {100},
number = {4},
pages = {1-6},
month = {August},
note = {Full text available}
}
Abstract
Persian (Farsi) language named entity recognition is a challenging, difficult, yet important task in natural language processing. This paper presents an approach based on a Local Filters model to recognize Persian (Farsi) language named entities. It uses multiple dictionaries, which are freely available on the Web. A dictionary is a collection of phrases that describe named entities. The framework is composed of two stages: (1) detection of named entity candidates using dictionaries for lookups and (2) filtering of false positives based. Dictionary lookups are performed using an efficient prefix-tree data structure. Our dictionary ?? based recognizer performs on Persian (Farsi) language with up to 88. 95% precision, 79. 65% recall, and an 82. 73% F1 score using ASEM.
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