NLP: Rule Based Name Entity Recognition
N. Kannaiya Raja1, Naol Bakala2, S. Suresh3

1Dr. N. Kannaiya Raja, M.E., Phd.,,Professor, Department of Computer Science, Ambo University, Ambo, Ethiopia.
2Mr. Naol Bakala, M.Sc., Head/Department of Computer Science, Ambo University.
3Mr. S. Suresh, M.E., Asst. Professor, Asst Professor/ Department of Computer Science & Engineering, C. Abdul Hakeem College of Engineering & Technology, Vellore, Tamil Nadu, India.
Manuscript received on 27 August 2019. | Revised Manuscript received on 07 September 2019. | Manuscript published on 30 September 2019. | PP: 4285-4290 | Volume-8 Issue-11, September 2019. | Retrieval Number: K20470981119/2019©BEIESP | DOI: 10.35940/ijitee.K2047.0981119
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Abstract: Named Entity Recognition (NER) is an information extraction task aimed at identifying and classifying words of a sentence, a paragraph or a document into predefined categories of Named Entities (NEs). NEs are terms that are used to name a person, location or organization. They are also used to refer to the value or amount of something. NER is an important tool in almost all NLP application areas out of which it is very essential in Search Engines (Semantic based), Machine Translation, and Question-Answering, Indexing for Information Retrieval and Automatic Summarization systems. This paper presents Rule-based approach for the development of Named Entity Recognition (NER) system for Afan Oromo language.
Keywords: Natural Language Process, Named Entity Recognition, Rule Based Approach.
Scope of the Article: Natural Language Processing