[Adapt] [Seminar] Knowledge Base Question Answering via Encoding of Complex Query Structures
luo.kangqi at qq.com
Wed Sep 12 11:16:06 CST 2018
In our weekly seminar today, I'll give a talk on my paper "Knowledge Base Question Answering via Encoding of Complex Query Structures" accepted in EMNLP 2018.
The goal of KBQA is to answer natural language questions which ask existing facts of some specific entities in the knowledge base. We attempt to solve the KBQA problem in a more complex scenario, where multiple entities and relations are involved in one question. In this work, we encode the complex query structure of a question into a uniform vector representation, and thus successfully capture the interactions between individual semantic components within a complex question. Experimental results on multiple KBQA datasets proved the effectiveness of our approach.
Time: Sept 12nd, 5pm (Wed, today)
Venue: Room 3-517A
See you there!
Kangqi Luo, PhD Candidate
ADAPT Lab, Department of Computer Science
SEIEE 3-341, Shanghai Jiao Tong University,
No. 800 Dongchuan Road, Shanghai, China
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