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Semantic parsing over multiple knowledge bases enables a parser to exploit structural similarities of programs across the multiple domains. However, the fundamental challenge lies in obtaining high-quality annotations of (utterance, program) pairs across various domains needed for training such models. To overcome this, we propose a novel framework to build a unified multi-domain enabled semantic parser trained only with weak supervision (denotations). Weakly supervised training is particularlydoi:10.18653/v1/p19-1473 dblp:conf/acl/AgrawalDJBMS19 fatcat:shwrsvoqfbag7kzhtrc7gvvm64