Journals Proceedings

Abstract

Named entities are phrases denoting the names of persons, locations, organizations etc. in text documents. These phrases are important for the access to document content, since they form the building blocks for the analysis of documents. Named Entity Recognition has applications in Natural Language Processing, document indexing, document annotation, translation, etc. NER plays an important role in various research areas of Natural Language Processing (NLP) like Question Answering and Summarization Systems, Information Retrieval, Machine Translation, Video Annotation, Semantic Web Search, Bioinformatics etc. The computational research of automatically identifying named entities in texts forms a vast and heterogeneous pool of strategies, methods and representations. In this paper, we will present an overview of the various methods used for implementing NER systems by giving the merits and demerits of each. We will also discuss some of the approaches suggested and implemented by NER system developers.