@InProceedings{nam-EtAl:2016:OKBQA2016,
  author    = {Nam, Sangha  and  Choi, GyuHyeon  and  Hahm, Younggyun  and  CHOI, KEY-SUN},
  title     = {SRDF: Extracting Lexical Knowledge Graph for Preserving Sentence Meaning},
  booktitle = {Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {77--81},
  abstract  = {In this paper, we present an open information extraction system so-called SRDF
	that generates lexical knowledge graphs from unstructured texts. In semantic
	web, knowledge is expressed in the RDF triple form but the natural language
	text consist of multiple relations between arguments. For this reason, we
	combine open information extraction with the reification for the full text
	extraction to preserve meaning of sentence in our knowledge graph. And also our
	knowledge graph is designed to adapt for many existing semantic web
	applications. At the end of this paper, we introduce the result of the
	experiment and a Korean template generation module developed using SRDF.},
  url       = {http://aclweb.org/anthology/W16-4411}
}