Persian Named Entity Recognition based with Local Filters
Morteza KolaliKhormuji, Mehrnoosh Bazrafkan · International Journal of Computer Applications · 2014
P ersian (F arsi) language named entity recognition is a challenging, difficult, yet important task in natural language processing.This paper presents an approach based on a Local F ilters model to recognize P ersian (F arsi) 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 P ersian (F arsi) language with up to 88.95% precision, 79.65% recall, and an 82.73% F1 score using ASEM.