Wei-Chuan Hsiao

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2017

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Integrating Subject, Type, and Property Identification for Simple Question Answering over Knowledge Base
Wei-Chuan Hsiao | Hen-Hsen Huang | Hsin-Hsi Chen
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

This paper presents an approach to identify subject, type and property from knowledge base (KB) for answering simple questions. We propose new features to rank entity candidates in KB. Besides, we split a relation in KB into type and property. Each of them is modeled by a bi-directional LSTM. Experimental results show that our model achieves the state-of-the-art performance on the SimpleQuestions dataset. The hard questions in the experiments are also analyzed in detail.
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