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Semantic parsing shines at analyzing complex natural language that involves composition and computation over multiple pieces of evidence. However, datasets for semantic parsing contain many factoid questions that can be answered from a single web document. In this paper, we propose to evaluate semantic parsing-based question answering models by comparing them to a question answering baseline that queries the web and extracts the answer only from web snippets, without access to the targetdoi:10.18653/v1/s17-1020 dblp:conf/starsem/TalmorGB17 fatcat:c6k5hlxp4fbs5nt464an72ukmm