Paper: A Probabilistic Forest-to-String Model for Language Generation from Typed Lambda Calculus Expressions

ACL ID D11-1149
Title A Probabilistic Forest-to-String Model for Language Generation from Typed Lambda Calculus Expressions
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

This paper describes a novel probabilistic ap- proach for generating natural language sen- tences from their underlying semantics in the form of typed lambda calculus. The approach is built on top of a novel reduction-based weighted synchronous context free grammar formalism, which facilitates the transforma- tion process from typed lambda calculus into natural language sentences. Sentences can then be generated based on such grammar rules with a log-linear model. To acquire such grammar rules automatically in an unsuper- vised manner, we also propose a novel ap- proach with a generative model, which maps from sub-expressions of logical forms to word sequences in natural language sentences. Ex- periments on benchmark datasets for both En- glish and Chinese generation tasks yield sig- nific...