Learning Dependency-Based Compositional Semantics

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Learning Dependency-Based Compositional Semantics
Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of the target logical forms. In this paper, we learn to map questions to answers via latent logical forms, which are induced automatically from question-answer pairs. In tackling this challenging learning problem, we introduce a new semantic representation which highlights a parallel between dependency syntax and efficient evaluation of logical forms. On two standard semantic parsing benchmarks (GEO and JOBS), our system obtains the highest published accuracies, despite using less supervision than existing systems.
Percy Liang, Michael I. Jordan, Dan Klein
Added 23 Aug 2011
Updated 23 Aug 2011
Type Journal
Year 2011
Where ACL
Authors Percy Liang, Michael I. Jordan, Dan Klein
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