A Detailed Analysis of Core NLP for Information Extraction

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND NETWORKED COLLABORATIVE ENGINEERING VOL No 01 ISSUE No 01 ISSN 2581-3242, 2019

15 Pages Posted: 19 Jun 2019

See all articles by Simran Jolly

Simran Jolly

Manav Rachna International Institute of Research and Studies

Rashmi Agrawal

Manav Rachna International Institute of Research & Studies

Date Written: June 12, 2019

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

Suggested Citation

Jolly, Simran and Agrawal, Rashmi, A Detailed Analysis of Core NLP for Information Extraction (June 12, 2019). INTERNATIONAL JOURNAL OF MACHINE LEARNING AND NETWORKED COLLABORATIVE ENGINEERING VOL No 01 ISSUE No 01 ISSN 2581-3242, 2019, Available at SSRN: https://ssrn.com/abstract=3402755

Simran Jolly (Contact Author)

Manav Rachna International Institute of Research and Studies ( email )

Manav Rachna Campus Rd
Sector 43
Gadakhor Basti Village, Haryana 121010
India

Rashmi Agrawal

Manav Rachna International Institute of Research & Studies ( email )

Delhi Suraj Kund Road
Sector 43
Faridabad, Haryana 121004
India

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