Abstract. Semantic parsing is the task of mapping a natural language sentence into a complete, formal meaning representation. Over the past decade, we have developed a number of machine learning methods for inducing semantic parsers by training on a corpus of sentences paired with their meaning representations in a specified formal language. We have demonstrated these methods on the automated construction of naturallanguage interfaces to databases and robot command languages. This paper reviews our prior work on this topic and discusses directions for future research.
Mooney REF studied the task of semantic parsing which aimed to map a natural language sentence into a complete, formal meaning representation.
Learning for semantic parsing
IN COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE
Computer Science