Humans communicate using natural language. We need to make sure that computers can
understand us so that they can act on our spoken commands or independently gain new …

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 …

We present an approach to training a joint syntactic and semantic parser that combines
syntactic training information from CCGbank with semantic training information from a …

In this thesis, we investigate an approach for grammar induction that relies on semantics to
drive the automatic learning of syntax rules. Specifically, we develop a semantic parser …

Semantic parsing, the study of translating natural language utterances into machine-
executable programs, is a well-established research area and has applications in question …

We present a new approach to learning a semantic parser (a system that maps natural
language sentences into logical form). Unlike previous methods, it exploits an existing …

A long-standing goal for the field of artificial intelligence is to enable computer
understanding of human languages. A core requirement in reaching this goal is the ability to …

Computational systems that learn to transform naturallanguage sentences into semantic
representations have important practical applications in building naturallanguage interfaces …

This paper presents a semantic parser that transforms an initial semantic hypothesis into the
correct semantics by applying an ordered list of transformation rules. These rules are learnt …

Syntactic parsing is one of the best understood language processing applications. Since
language and grammar have been formally defined, it is easy for computers to parse the …