A Survey on Complex Question Answering over Knowledge Base: Recent
Advances and Challenges
- URL: http://arxiv.org/abs/2007.13069v1
- Date: Sun, 26 Jul 2020 07:13:32 GMT
- Title: A Survey on Complex Question Answering over Knowledge Base: Recent
Advances and Challenges
- Authors: Bin Fu, Yunqi Qiu, Chengguang Tang, Yang Li, Haiyang Yu, Jian Sun
- Abstract summary: Question Answering (QA) over Knowledge Base (KB) aims to automatically answer natural language questions.
Researchers have shifted their attention from simple questions to complex questions, which require more KB triples and constraint inference.
- Score: 71.4531144086568
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Question Answering (QA) over Knowledge Base (KB) aims to automatically answer
natural language questions via well-structured relation information between
entities stored in knowledge bases. In order to make KBQA more applicable in
actual scenarios, researchers have shifted their attention from simple
questions to complex questions, which require more KB triples and constraint
inference. In this paper, we introduce the recent advances in complex QA.
Besides traditional methods relying on templates and rules, the research is
categorized into a taxonomy that contains two main branches, namely Information
Retrieval-based and Neural Semantic Parsing-based. After describing the methods
of these branches, we analyze directions for future research and introduce the
models proposed by the Alime team.
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