NER using machine learning approaches

Named Entity Recognition (NER) is a subtask of information extraction task that seeksto identify and classify parts in text that consult with predefind classessuch as person names, organisations, places, time expressions, quantities and monetary values. This paper gives the detailed of various approaches and techniques that are used for Named Entity Recognition, that identifies the named entities from the given knowledge. It explains the different machine learning models that are employed in the Named Entity Recognition. The performances of varied Named Entity Recognition systems that are developed using machine learning models are reviewed. Further, we examine the area and domain of its potential and conventional usage in modern times. We lastly conclude our multifaceted study by mentioning some of the common challenges that are found in the NER technology and suggest some practical solutions for improving the same.