@inproceedings{hahm-etal-2014-named,
title = "Named Entity Corpus Construction using {W}ikipedia and {DB}pedia Ontology",
author = "Hahm, Younggyun and
Park, Jungyeul and
Lim, Kyungtae and
Kim, Youngsik and
Hwang, Dosam and
Choi, Key-Sun",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/688_Paper.pdf",
pages = "2565--2569",
abstract = "In this paper, we propose a novel method to automatically build a named entity corpus based on the DBpedia ontology. Since most of named entity recognition systems require time and effort consuming annotation tasks as training data. Work on NER has thus for been limited on certain languages like English that are resource-abundant in general. As an alternative, we suggest that the NE corpus generated by our proposed method, can be used as training data. Our approach introduces Wikipedia as a raw text and uses the DBpedia data set for named entity disambiguation. Our method is language-independent and easy to be applied to many different languages where Wikipedia and DBpedia are provided. Throughout the paper, we demonstrate that our NE corpus is of comparable quality even to the manually annotated NE corpus.",
}
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<abstract>In this paper, we propose a novel method to automatically build a named entity corpus based on the DBpedia ontology. Since most of named entity recognition systems require time and effort consuming annotation tasks as training data. Work on NER has thus for been limited on certain languages like English that are resource-abundant in general. As an alternative, we suggest that the NE corpus generated by our proposed method, can be used as training data. Our approach introduces Wikipedia as a raw text and uses the DBpedia data set for named entity disambiguation. Our method is language-independent and easy to be applied to many different languages where Wikipedia and DBpedia are provided. Throughout the paper, we demonstrate that our NE corpus is of comparable quality even to the manually annotated NE corpus.</abstract>
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%0 Conference Proceedings
%T Named Entity Corpus Construction using Wikipedia and DBpedia Ontology
%A Hahm, Younggyun
%A Park, Jungyeul
%A Lim, Kyungtae
%A Kim, Youngsik
%A Hwang, Dosam
%A Choi, Key-Sun
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F hahm-etal-2014-named
%X In this paper, we propose a novel method to automatically build a named entity corpus based on the DBpedia ontology. Since most of named entity recognition systems require time and effort consuming annotation tasks as training data. Work on NER has thus for been limited on certain languages like English that are resource-abundant in general. As an alternative, we suggest that the NE corpus generated by our proposed method, can be used as training data. Our approach introduces Wikipedia as a raw text and uses the DBpedia data set for named entity disambiguation. Our method is language-independent and easy to be applied to many different languages where Wikipedia and DBpedia are provided. Throughout the paper, we demonstrate that our NE corpus is of comparable quality even to the manually annotated NE corpus.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/688_Paper.pdf
%P 2565-2569
Markdown (Informal)
[Named Entity Corpus Construction using Wikipedia and DBpedia Ontology](http://www.lrec-conf.org/proceedings/lrec2014/pdf/688_Paper.pdf) (Hahm et al., LREC 2014)
ACL
- Younggyun Hahm, Jungyeul Park, Kyungtae Lim, Youngsik Kim, Dosam Hwang, and Key-Sun Choi. 2014. Named Entity Corpus Construction using Wikipedia and DBpedia Ontology. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2565–2569, Reykjavik, Iceland. European Language Resources Association (ELRA).