SParC: Cross-Domain Semantic Parsing in Context

The most prominent context-dependent text-to-SQL benchmark is ATIS1, which is set in the flight-booking domain and contains only one database (Hemphill et al., 1990; Dahl et al., 1994). In a real-world setting, users tend to ask a sequence of thematically related questions to learn about a particular topic or to achieve a complex goal. Previous studies have shown that by allowing questions to be constructed sequentially, users can explore the data in a more flexible manner, which reduces their cognitive burden (Hale, 2006; Levy, 2008; Frank, 2013; Iyyer et al., 2017) and increases their involvement when interacting with the system. The phrasing of such questions depends heavily on the interaction history (Kato et al., 2004; Chai and Jin, 2004; Bertomeu et al., 2006). The users may explicitly refer to or omit previously mentioned entities and constraints, and may introduce refinements, additions or substitutions to what has already been said (Figure 1).