As mentioned earlier, existing solutions that depend on predefined templates (such as (Xu et al., 2016;Bast and Haussmann, 2015)) or query graph structure patterns (such as (Yih et al., 2015)) may not be suitable due to the diversity of complex questions.
considering the above challenges, we propose a state transition based framework to translate users' question N into a semantic query graph (SQG) Q S , further the answers of N can be found by matching Q S over the knowledge graph G. we first recognize nodes (such as entities and variables) from N as the initial state (Section 2.1).