Named entity recognition and classification for Gujarati language

Abstract

Named Entity Recognition (NER) is a method to search for a particular Named Entity (NE)[1] from a file or an image, recognize it and classify it into specified Entity Classes like Name, Location, Organization, Numbers and Others Categories. It is the most useful element of the technique known as Natural Language Processing (NLP) which makes text extraction very easy [2]. In this paper, we focus on using Hidden Markov Model (HMM) based techniques to recognize the Named Entity (NE) for Gujarati language. The main aim of using HMM is that it provides better performance and can be easily implemented for any languages. A remarkable amount of work has been carried out for many languages like English, Greek, Chinese etc. But, still a wide scope is open for Indian Origin Languages like Hindi, Gujarati, Devanagari etc. As Gujarati is not only the Indian Language, but a language that is most spoken in Gujarat. Thus, in this paper, we emphasis on proposing a NER based scheme for Gujarati Language using HMM.