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Large-scale Semantic Parsing without Question-Answer Pairs


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. 

PDF (presented at NAACL 2015)

Author Biography

Siva Reddy

School of Informatics, PhD Student

Mirella Lapata

School of Informatics, Professor

Mark Steedman

School of Informatics, Professor