Abstract
In this paper, we present a novel lexical knowledge graph called SRDF and describe an extraction system that automatically generates a SRDF graph from the Korean natural language sentence. In the semantic web, knowledge is expressed in the RDF triple form but natural language sentences consist of multiple relationships between the predicates and arguments. For this reason, we design a SRDF graph structure that combines open information extraction method with reification for the whole sentence knowledge extraction. In addition, to add semantics to a SRDF graph, we establish a link between the lexical argument and entity in ontological knowledge base using the Entity Linking system. The proposed knowledge graph is adaptable for many existing semantic web applications. We present the results of an experimental evaluation and demonstrate the use of SRDF graph in developing a Korean SPARQL template generation module in the OKBQA platform.
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Notes
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Specifically, we used ETRI Korean NLP tool.
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Acknowledgements
This work was supported by an Institute for Information & communications Technology Promotion (IITP) grant funded by the Korean government (MSIP) (2013-0-00109, WiseKB: Big data based self-evolving knowledge base and reasoning platform). This work was supported by an Industrial Strategic technology development program (10072064, Development of Novel Artificial Intelligence Technologies To Assist Imaging Diagnosis of Pulmonary, Hepatic, and Cardiac Diseases and Their Integration into Commercial Clinical PACS Platforms) funded by the Ministry of Trade Industry and Energy (MI, Korea). This work was supported by the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP (2015M3A9A7029735). This work was supported by an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (R0124-16-0002, Emotional Intelligence Technology to Infer Human Emotion and Carry on Dialogue Accordingly).
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Nam, S., Choi, G., Choi, KS. (2017). SRDF: A Novel Lexical Knowledge Graph for Whole Sentence Knowledge Extraction. In: Gracia, J., Bond, F., McCrae, J., Buitelaar, P., Chiarcos, C., Hellmann, S. (eds) Language, Data, and Knowledge. LDK 2017. Lecture Notes in Computer Science(), vol 10318. Springer, Cham. https://doi.org/10.1007/978-3-319-59888-8_27
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