Towards an efficient Malayalam Named Entity Recognizer Analysis on the Challenges

Abstract

Abstract Named Entity Recognition (NER) also known as entity extraction plays an important role in identifying and classifying the named entities into different categories like name of person, place, organization, things, quantity, monetary value etc. that appear in a document. NER has applications in various Natural Language Processing (NLP) tasks such as information retrieval, question answering system, Machine Translation, Sentiment Analysis. NER systems can be developed using rule based, machine learning or hybrid approach. Now Deep learning is being used to develop efficient NER as these models are capable of learning patterns easily and efficiently. Quite a large number of work has been done in English compared to the work done for Indian Languages. The focus of this paper is to highlight the challenges in building an efficient NER for one of the south Indian language namely Malayalam. The different issues that we need to address in order to develop an efficient NER for Malayalam is presented.