GraphQ IR: Unifying Semantic Parsing of Graph Query Language with Intermediate Representation. (arXiv:2205.12078v1 [cs.CL])

Subject to the semantic gap lying between natural and formal language, neural
semantic parsing is typically bottlenecked by the paucity and imbalance of
data. In this paper, we propose a unified intermediate representation (IR) for
graph query languages, namely GraphQ IR. With the IR's natural-language-like
representation that bridges the semantic gap and its formally defined syntax
that maintains the graph structure, neural semantic parser can more effectively
convert user queries into our GraphQ IR, which can be later automatically
compiled …

arxiv graph language parsing query representation semantic