A Korean Knowledge Extraction System for Enriching a KBox

Sangha Nam, Eun-kyung Kim, Jiho Kim, Yoosung Jung, Kijong Han, Key-Sun Choi


Abstract
The increased demand for structured knowledge has created considerable interest in knowledge extraction from natural language sentences. This study presents a new Korean knowledge extraction system and web interface for enriching a KBox knowledge base that expands based on the Korean DBpedia. The aim is to create an endpoint where knowledge can be extracted and added to KBox anytime and anywhere.
Anthology ID:
C18-2005
Volume:
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
20–24
Language:
URL:
https://www.aclweb.org/anthology/C18-2005
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/C18-2005.pdf