Open AccessKorean Coreference Resolution with Guided Mention Pair Model Using Deep Learning
Author(s) -
Park Cheoneum,
Choi KyoungHo,
Lee Changki,
Lim Soojong
Publication year - 2016
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.16.0115.0896
Subject(s) - coreference , computer science , artificial intelligence , deep learning , resolution (logic) , natural language processing , machine learning , feature engineering , information extraction
The general method of machine learning has encountered disadvantages in terms of the significant amount of time and effort required for feature extraction and engineering in natural language processing. However, in recent years, these disadvantages have been solved using deep learning. In this paper, we propose a mention pair (MP) model using deep learning, and a system that combines both rule‐based and deep learning‐based systems using a guided MP as a coreference resolution, which is an information extraction technique. Our experiment results confirm that the proposed deep‐learning based coreference resolution system achieves a better level of performance than rule‐ and statistics‐based systems applied separately.