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Reseach Article

Conditional Random Field Based Named Entity Recognition in Geological text

by Sobhana N.V, Pabitra Mitra, S.K. Ghosh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 3
Year of Publication: 2010
Authors: Sobhana N.V, Pabitra Mitra, S.K. Ghosh
10.5120/72-166

Sobhana N.V, Pabitra Mitra, S.K. Ghosh . Conditional Random Field Based Named Entity Recognition in Geological text. International Journal of Computer Applications. 1, 3 ( February 2010), 119-125. DOI=10.5120/72-166

@article{ 10.5120/72-166,
author = { Sobhana N.V, Pabitra Mitra, S.K. Ghosh },
title = { Conditional Random Field Based Named Entity Recognition in Geological text },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 3 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 119-125 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number3/72-166/ },
doi = { 10.5120/72-166 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:44:06.923550+05:30
%A Sobhana N.V
%A Pabitra Mitra
%A S.K. Ghosh
%T Conditional Random Field Based Named Entity Recognition in Geological text
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 3
%P 119-125
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper describes about the development of a Named Entity Recognition (NER) system for Geological text using Conditional Random Fields (CRFs). The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the various named entity (NE) classes. The NE tagged geological corpus was developed from the collection of scientific reports and articles on the geology of the Indian subcontinent has been used to build up the system. The training set consists of more than 2 lakh words and has been manually annotated with a NE tag set of seventeen tags. The system is able to recognize 17 classes of NEs with 75.8% F-measure.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Geological Corpus Named Entity Recognition Precision Recall F-measure Geographic references