• Aashima Saxena
• Sanjay Kumar Malik

The goal of web semantics is to convert unstructured data to meaningful representation, which may be largely benefited by exploiting many techniques like natural language processing (NLP). NLP plays a significant role in understanding, analyzing and generating techniques like information extraction, parsing and semantic analysis. NLP models and Semantic Web support each other and have complementary roles in data management. In this paper, first NLP and its techniques have been revisited and its role has been discussed. Second, NLP pre-processing pipeline has been explored and a stack for the same has been presented. Third, a few significant NLP toolkits and the challenges faced during implementation have been explored. Fourth, OpenNLP has been used to realize a few components of the NLP pre-processing pipeline like tokenizer, parsing and sentence splitter. Finally, the last section concludes the paper and future work has been stated.

Natural Language Processing, semantic web, openNLP, parsing, NLP pipeline.

"Using OpenNLP for Realizing Natural Language Pre-Processing Pipeline as an Interface towards Semantic Web ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.10-14, December-2018, Available :http://www.jetir.org/papers/JETIR1812202.pdf

"Using OpenNLP for Realizing Natural Language Pre-Processing Pipeline as an Interface towards Semantic Web ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp10-14, December-2018, Available at : http://www.jetir.org/papers/JETIR1812202.pdf