Chinese Knowledge Base Question Answering by Attention-Based Multi-Granularity Model

Chinese Knowledge Base Question Answering by Attention-Based Multi-Granularity Model

Chinese knowledge base question answering (KBQA) is designed to answer the questions with the facts contained in a knowledge base. This task can be divided into two subtasks: topic entity extraction and relation selection. During the topic entity extraction stage, an entity extraction model is built...

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Bibliographic Details
Main Authors: Cun Shen, Tinglei Huang, Xiao Liang, Feng Li, Kun Fu
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Information
Subjects:
knowledge base question answering
topic entity extraction
relation selection
multi-granularity embeddings
attention mechanism
Online Access:http://www.mdpi.com/2078-2489/9/4/98

Internet

http://www.mdpi.com/2078-2489/9/4/98

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