* logical approaches rely on techniques from proof theory and model-theoretic semantics; primarily concerned with inference, ambiguity, vagueness, and compositional interpretation
* statistical approaches derive their tools from algorithms and optimization and tend to focus on word meanings, vector space models, and other broad notions of semantic content
* principle of compositionality: meaning of complex syntactic phrase is function of meanings of its constituent phrases
* heart of grammar is its lexicon
* generate a grammar exponential in the length of the sentence; dynamic programming can mitigate problems for parsing
* learning via denotations in general results in increased computational complexity
* learning from denotations offers advantage of being able to define features on denotations
* semantic representations can also be distributed representations (rather than logical forms)