Named Entity Recognition in Natural languages using Hidden Markov Mode

Named Entity Recognition (NER) aims to detect and categorize named entities in a document into certain predefined named entities classes such as Name of Person Location Organization River Location Expressions of times Quantities Monetary value Percentages etc. In the nomenclature of computational linguistics tasks Named Entity Recognition lies in the domain of information extraction which detect definite kinds of information from documents as opposed to the more general task of document management which seeks to extract all of the information found in a document Named Entity Recognition in Indian Languages is a very problematical task. Since In English and in Other European Languages the method of Capitalization makes it easy to identify the Proper Nouns in a document which is not so in case of Indian Languages. Moreover Indian languages are free order and highly inflectional and morphologically rich in nature. I have performed NER using HMM in following Natural Languages: Hindi Bengali Telugu Urdu Marathi Punjabi English and French. I have also dealt with problem of Unknown words in Named Entity Recognition using Transliteration.