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:
- PDF:
- http://aclanthology.lst.uni-saarland.de/C18-2005.pdf