Large-scale Semantic Parsing without Question-Answer Pairs

Siva Reddy, Mirella Lapata, Mark Steedman

Abstract


In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a graph matching problem. Our model converts sentences to semantic graphs using CCG and subsequently grounds them to Freebase guided by denotations as a form of weak supervision. Evaluation experiments on a subset of the FREE917 and WEBQUESTIONS benchmark datasets show our semantic parser improves over the state of the art. 


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