Named Entity Recognition and classification is the task of identifying the text of special meaning and classifying into some predetermined categories. These categories may range from person, location, organization to dates, quantities, numeric expressions etc. Named entity recognition has been an important research area since 1996.Still it is a required field to be studied due to its important use in various natural language applications.
Named Entity Recognition (NER) aims to recognize mentions of rigid designators from text belonging to named entity types such as persons, locations, organizations etc. [1]. It has many applications. It acts as a standalone tool for information extraction and filtering. It also plays a key role in various natural language applications such as question answering, machine translation, automatic text summarization etc. Evolution of NER. The term “Named Entity” was first used at the sixth Message Understanding Conference (MUC-6), as the task of identifying names of organizations, people and geographic locations in text, as well as currency, time and percentage expressions. Since MUC- 6 there has been increasing interest in NER, and various scientific events devote much effort to this topic.
Named-Entity Recognition 