A Study on the Named Entity Recognition and Classification

Justus Selwyn

Abstract


The objective of this paper is to summarize twenty five years of research in the Named Entity Recognition and Classification (NERC) field, from 1991 to 2016.

Methods: This survey records observations about history of NERC and domains, languages and named entity types studied in the literature. To begin with, manually written rules are used to develop NERC systems, but of late machine learning is used to improve them. Those techniques and evaluation methods are presented here. Findings: This survey of NERC helped us to proceed further in designing a framework for knowledge visualization. 


Keywords


Bootstrapping, Enamex, Machine learning, Named entity extraction

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