Summary of the paper

Title Named Entity Corpus Construction using Wikipedia and DBpedia Ontology
Authors Younggyun Hahm, Jungyeul Park, Kyungtae Lim, Youngsik Kim, Dosam Hwang and Key-Sun Choi
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.
Topics Named Entity Recognition, Linked Data
Full paper Named Entity Corpus Construction using Wikipedia and DBpedia Ontology
Bibtex @InProceedings{HAHM14.688,
  author = {Younggyun Hahm and Jungyeul Park and Kyungtae Lim and Youngsik Kim and Dosam Hwang and Key-Sun Choi},
  title = {Named Entity Corpus Construction using Wikipedia and DBpedia Ontology},
  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}
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