N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format. / Röder, Michael; Usbeck, Ricardo; Hellmann, Sebastian et al.
Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. ed. / Nicoletta Calzolari; Khalid Choukri; Sara Goggi; Thierry Declerck; Joseph Mariani; Bente Maegaard; Asuncion Moreno; Jan Odijk; Helene Mazo; Stelios Piperidis; Hrafn Loftsson. Reykjavik, Iceland: European Language Resources Association (ELRA), 2014. p. 3529-3533 (Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Röder, M, Usbeck, R, Hellmann, S, Gerber, D & Both, A 2014, N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format. in N Calzolari, K Choukri, S Goggi, T Declerck, J Mariani, B Maegaard, A Moreno, J Odijk, H Mazo, S Piperidis & H Loftsson (eds), Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014, European Language Resources Association (ELRA), Reykjavik, Iceland, pp. 3529-3533, 9th International Conference on Language Resources and Evaluation, LREC 2014, Reykjavik, Iceland, 26.05.14. <https://aclanthology.org/L14-1662/>

APA

Röder, M., Usbeck, R., Hellmann, S., Gerber, D., & Both, A. (2014). N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format. In N. Calzolari, K. Choukri, S. Goggi, T. Declerck, J. Mariani, B. Maegaard, A. Moreno, J. Odijk, H. Mazo, S. Piperidis, & H. Loftsson (Eds.), Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014 (pp. 3529-3533). (Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014). European Language Resources Association (ELRA). https://aclanthology.org/L14-1662/

Vancouver

Röder M, Usbeck R, Hellmann S, Gerber D, Both A. N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format. In Calzolari N, Choukri K, Goggi S, Declerck T, Mariani J, Maegaard B, Moreno A, Odijk J, Mazo H, Piperidis S, Loftsson H, editors, Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. Reykjavik, Iceland: European Language Resources Association (ELRA). 2014. p. 3529-3533. (Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014).

Bibtex

@inbook{2a893794b7f64b678dfd8ff257522d90,
title = "N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format",
abstract = "Extracting Linked Data following the Semantic Web principle from unstructured sources has become a key challenge for scientific research. Named Entity Recognition and Disambiguation are two basic operations in this extraction process. One step towards the realization of the Semantic Web vision and the development of highly accurate tools is the availability of data for validating the quality of processes for Named Entity Recognition and Disambiguation as well as for algorithm tuning. This article presents three novel, manually curated and annotated corpora (N3). All of them are based on a free license and stored in the NLP Interchange Format to leverage the Linked Data character of our datasets.",
keywords = "Datasets, Named entity detection, Named entity disambiguation, NLP interchange format, Informatics, Business informatics",
author = "Michael R{\"o}der and Ricardo Usbeck and Sebastian Hellmann and Daniel Gerber and Andreas Both",
note = "We thank Luise Erfurth and Didier Cherix for helping us creating annotations of the datasets and Jens Lehmann for his feedback. A special thanks goes to news.de for allowing us to use their articles. Parts of this work were supported by the ESF and the Free State of Saxony. ACL materials are Copyright {\textcopyright} 1963–2023; 9th International Conference on Language Resources and Evaluation, LREC 2014, LREC 2014 ; Conference date: 26-05-2014 Through 31-05-2014",
year = "2014",
month = may,
language = "English",
series = "Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014",
publisher = "European Language Resources Association (ELRA)",
pages = "3529--3533",
editor = "Nicoletta Calzolari and Khalid Choukri and Sara Goggi and Thierry Declerck and Joseph Mariani and Bente Maegaard and Asuncion Moreno and Jan Odijk and Helene Mazo and Stelios Piperidis and Hrafn Loftsson",
booktitle = "Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014",
address = "Luxembourg",
url = "http://www.lrec-conf.org/proceedings/lrec2014/index.html",

}

RIS

TY - CHAP

T1 - N3 - A collection of datasets for named entity recognition and disambiguation in the NLP interchange format

AU - Röder, Michael

AU - Usbeck, Ricardo

AU - Hellmann, Sebastian

AU - Gerber, Daniel

AU - Both, Andreas

N1 - Conference code: 9

PY - 2014/5

Y1 - 2014/5

N2 - Extracting Linked Data following the Semantic Web principle from unstructured sources has become a key challenge for scientific research. Named Entity Recognition and Disambiguation are two basic operations in this extraction process. One step towards the realization of the Semantic Web vision and the development of highly accurate tools is the availability of data for validating the quality of processes for Named Entity Recognition and Disambiguation as well as for algorithm tuning. This article presents three novel, manually curated and annotated corpora (N3). All of them are based on a free license and stored in the NLP Interchange Format to leverage the Linked Data character of our datasets.

AB - Extracting Linked Data following the Semantic Web principle from unstructured sources has become a key challenge for scientific research. Named Entity Recognition and Disambiguation are two basic operations in this extraction process. One step towards the realization of the Semantic Web vision and the development of highly accurate tools is the availability of data for validating the quality of processes for Named Entity Recognition and Disambiguation as well as for algorithm tuning. This article presents three novel, manually curated and annotated corpora (N3). All of them are based on a free license and stored in the NLP Interchange Format to leverage the Linked Data character of our datasets.

KW - Datasets

KW - Named entity detection

KW - Named entity disambiguation

KW - NLP interchange format

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=85032871168&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/0861e4d8-9e27-347c-b695-bfba479f1be1/

M3 - Article in conference proceedings

AN - SCOPUS:85032871168

T3 - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014

SP - 3529

EP - 3533

BT - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014

A2 - Calzolari, Nicoletta

A2 - Choukri, Khalid

A2 - Goggi, Sara

A2 - Declerck, Thierry

A2 - Mariani, Joseph

A2 - Maegaard, Bente

A2 - Moreno, Asuncion

A2 - Odijk, Jan

A2 - Mazo, Helene

A2 - Piperidis, Stelios

A2 - Loftsson, Hrafn

PB - European Language Resources Association (ELRA)

CY - Reykjavik, Iceland

T2 - 9th International Conference on Language Resources and Evaluation, LREC 2014

Y2 - 26 May 2014 through 31 May 2014

ER -

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