A Detailed Analysis of Core NLP for Information Extraction
International Journal of Machine Learning and Networked Collaborative Engineering, 1(01), 33-47, 2018
15 Pages Posted: 28 May 2019
Date Written: March 22, 2018
The amount of unstructured text present in all electronic media is increasing periodically day after day. In order to extract relevant and succinct information, extraction algorithms are limited to entity relationships. This paper is compendium of different bootstrapping approaches which have their own subtask of extracting dependencies like who did, what, whom, from natural language sentence. This can be extremely helpful in both feature design and error analysis in application of machine learning to natural language processing.
Keywords: Bootstrapping, Language, Lexicon, Unstructured, Corpus, Domain
JEL Classification: Machine Learning, NLP
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