Paper Info
Title
Named Entity Corpus Construction using Wikipedia and DBpedia Ontology.
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.
Year
Venue
Keywords
2014
LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Corpus,Named Entity Recognition,Linked Data
Field
DocType
Citations 
Training set,Entity linking,Ontology,Annotation,Information retrieval,Computer science,Named entity,Artificial intelligence,Natural language processing,Named-entity recognition
Conference
4
PageRank 
References 
Authors
0.49
10
6
Name
Order
Citations
PageRank
YoungGyun Hahm175.02
Jungyeul Park2198.13
Kyungtae Lim352.91
Young-Sik Kim439454.26
Dosam Hwang512127.27
Key-Sun Choi6893127.32