Named Entity Corpus Construction using Wikipedia and DBpedia Ontology

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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.
Publisher
Language Resources and Evaluation Conference
Issue Date
2014-05-26
Language
English
Citation

the 9th Language Resources and Evaluation Conference (LREC), 2014

URI
http://hdl.handle.net/10203/211425
Appears in Collection
CS-Conference Papers(학술회의논문)
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