A Detailed Analysis of Core NLP for Information Extraction

Abstract

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