Summary of the paper
| Title | Benchmarking the Extraction and Disambiguation of Named Entities on the Semantic Web |
|---|---|
| Authors | Giuseppe Rizzo, Marieke Van Erp and Raphaël Troncy |
| Abstract | Named entity recognition and disambiguation are of primary importance for extracting information and for populating knowledge bases. Detecting and classifying named entities has traditionally been taken on by the natural language processing community, whilst linking of entities to external resources, such as those in DBpedia, has been tackled by the Semantic Web community. As these tasks are treated in different communities, there is as yet no oversight on the performance of these tasks combined. We present an approach that combines the state-of-the art from named entity recognition in the natural language processing domain and named entity linking from the semantic web community. We report on experiments and results to gain more insights into the strengths and limitations of current approaches on these tasks. Our approach relies on the numerous web extractors supported by the NERD framework, which we combine with a machine learning algorithm to optimize recognition and linking of named entities. We test our approach on four standard data sets that are composed of two diverse text types, namely newswire and microposts. |
| Topics | Linked Data, Web Services |
Full paper  |
Benchmarking the Extraction and Disambiguation of Named Entities on the Semantic Web |
| Bibtex | @InProceedings{RIZZO14.176, author = {Giuseppe Rizzo and Marieke Van Erp and Raphaël Troncy}, title = {Benchmarking the Extraction and Disambiguation of Named Entities on the Semantic Web}, 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} } |