• Janani R
• Dr.S.Vijayarani

To extract the important information from natural text, recognition of exact entities such as person, place, organization, concept and locations is very useful. Learning to extract names in natural language text is called Named Entity Recognition (NER) task. It is used to solve the problems in the area of Information Retrieval, Machine Translation, Text Summarization and Web Search. For NER, the number of open source tools are available. The main aim of this research work is to analyze the performance of nine open source NER tools. They are Dandelion API, spaCy, Stanford Named Entity Tagger, ParallelDots, Text Analysis API, displaCy Named Entity Visualizer, TextRazor, Cognitive Computing Group and NLTK. Based on the results, it is observed that the Dandelion API tool gives the better performance when compared to other tools.

NLP, Named Entity, Entity Recognition, Open Source Tools, Information Extraction, Information Retrieval

"Natural Language Processing: An Analysis of Open Source Named Entity Recognition Tools", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.566-575, February-2019, Available :http://www.jetir.org/papers/JETIR1902076.pdf

"Natural Language Processing: An Analysis of Open Source Named Entity Recognition Tools", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp566-575, February-2019, Available at : http://www.jetir.org/papers/JETIR1902076.pdf