الفهرس 
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Abstract
This paper introduces a multithreading named entity recognition (NER) by using the pooling technique and get benefits of its computation time in the NER. NER is a sub problem of many natural language processing task such as information extraction. NER is used to identify expressions that refer to person, location, organization, number, date, e-mail, and so on from structured and unstructured documents. Handcrafted approaches required human intuition and large number of rule to write simple approach for recognize named entity. So using machine learning approach (Supervised learning). Feature selection is used to determine the necessary feature to use. It is useful for reducing number of features reduce execution time and the cost of recognition. The paper used GATE which consider a collection of machine learning algorithms. In this paper, we develop Gate by embedded Gate in java and using pooling technique to enhance the computation time. This allow us to analysis a large corpus and classify the named entity in a little time. This program will run faster and make better use of the multiple CPU/core architecture.