期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：9
页码：8012-8015
出版社：IJECS
摘要：This paper present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approachlearns from natural language sentences paired with world states consisting of multiple potential logical meaning representations. Itdisambiguates the meaning of each sentence while simultaneously learning a semantic parser that maps sentences into logical form.Compared to a previous generative model for semantic alignment, it also supports full semantic parsing
关键词：Language Genertaor;Ambiguity; probabilistic;generative model ;Ontology; ; Distributional Semantics
