Research Article
Persian Named Entity Recognition based with Local Filters
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 100 - Issue 4 |
| Published: August 2014 |
| Authors: Morteza Kolali Khormuji, Mehrnoosh Bazrafkan |
10.5120/17510-8062
|
Morteza Kolali Khormuji, Mehrnoosh Bazrafkan . Persian Named Entity Recognition based with Local Filters. International Journal of Computer Applications. 100, 4 (August 2014), 1-6. DOI=10.5120/17510-8062
@article{ 10.5120/17510-8062,
author = { Morteza Kolali Khormuji,Mehrnoosh Bazrafkan },
title = { Persian Named Entity Recognition based with Local Filters },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 100 },
number = { 4 },
pages = { 1-6 },
doi = { 10.5120/17510-8062 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Morteza Kolali Khormuji
%A Mehrnoosh Bazrafkan
%T Persian Named Entity Recognition based with Local Filters%T
%J International Journal of Computer Applications
%V 100
%N 4
%P 1-6
%R 10.5120/17510-8062
%I Foundation of Computer Science (FCS), NY, USA
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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