An Emphatic Attempt with Cognizance of the Marathi Language for Named Entity Recognition.

Recent developments in the field of artificial intelligence has led to renewed interest in natural language processing. Named entity recognition (NER) is a classic problem in natural language processing. Investigating named entities is a continuing concern within information extraction. Names of people, organizations, locations, events, etc. are named entities (NEs). Although extensive research has been carried out on NER, limited study exists that explores NER in the Marathi language. The paper aims to provide a conceptual theoretical framework based on the gazetteer matching technique for named entity recognition system development for the Marathi language. A combination of rules and regular expressions is considered for temporal and numerical pattern recognition. The techniques presented in this paper are systematic, clear, and effective for morphologically rich language processing tool development. The system described in the paper reports a satisfactory performance with 62.64% NE identification and 72.27% NE classification accuracy. [ABSTRACT FROM AUTHOR]