Entity Linking Korean Text: An Unsupervised Learning Approach using Semantic Relations

Youngsik Kim, Key-Sun Choi


Anthology ID:
K15-1014
Volume:
Proceedings of the Nineteenth Conference on Computational Natural Language Learning
Month:
July
Year:
2015
Address:
Beijing, China
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
132–141
Language:
URL:
https://aclanthology.org/K15-1014
DOI:
10.18653/v1/K15-1014
Bibkey:
Cite (ACL):
Youngsik Kim and Key-Sun Choi. 2015. Entity Linking Korean Text: An Unsupervised Learning Approach using Semantic Relations. In Proceedings of the Nineteenth Conference on Computational Natural Language Learning, pages 132–141, Beijing, China. Association for Computational Linguistics.
Cite (Informal):
Entity Linking Korean Text: An Unsupervised Learning Approach using Semantic Relations (Kim & Choi, CoNLL 2015)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-2/K15-1014.pdf