* Supervised semantic parsers
* First must map questiosn into logical forms and this requires data with manually labeled semantic forms
* all we really care about is resulting denotation for a given input, so are free to choose how we represent logical forms
* introduce new semantic representation: dependency-based compositional semantics
* represent logical forms as DCS trees where nodes represent predicates (State, Country, Genus, ...) and edges represent relations 
* such a form allows for a transparency between syntactics and semantics and hence a streamlined framework for program induction
* denotation at root node
* trees mirror syntactic dependency structure, facilitating parsing but also enable efficient computation of denotations defined on a given tree
* to handle divergence between syntactic and semantic scope in some more complicated expressions, mark nodes low in tree with *mark* relation (E, Q, or C) and then invoke it higher up with *execute* relation to create desired semantic scope
* discriminative semantic parsing model placing a log-linear distribution over the set of permissible DCS trees given an utterance