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/works › Article in conference proceedings › Research › peer-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 -
