Summary of the paper
| Title | N³ - A Collection of Datasets for Named Entity Recognition and Disambiguation in the NLP Interchange Format |
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| Authors | Michael Röder, Ricardo Usbeck, Sebastian Hellmann, Daniel Gerber and andreas Both |
| 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. |
| Topics | Semantic Web, Standards for LRs |
Full paper  |
N³ - A Collection of Datasets for Named Entity Recognition and Disambiguation in the NLP Interchange Format |
| Bibtex | @InProceedings{RDER14.856, author = {Michael Röder and Ricardo Usbeck and Sebastian Hellmann and Daniel Gerber and andreas Both}, title = {N³ - A Collection of Datasets for Named Entity Recognition and Disambiguation in the NLP Interchange Format}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |