The interpretive challenges presented by such sentences are (or should be) of great concern in computational linguistics, since much of people's general knowledge about the world is most naturally expressed in the form of generic and habitual sentences. Systematic ways of interpreting and disambiguating such sentences would immediately provide a way of funneling large amounts of knowledge into formal knowledge bases from sources such as lexicons, encyclopedias, and crowd-sourced collections of generic claims such as those in Open Mind Common Sense (e.g., Singh et al. 2002; Lieberman et al. 2004; Havasi et al. 2007). Many theorists assume that the logical forms of such sentences should be tripartite structures with a quantifier that quantifies over objects or situations, a restrictor that limits the quantificational domain, and a nuclear scope (main clause) that makes an assertion about the elements of the domain (e.g., see Carlson 2011; Cohen 2002; or Carlson &amp; Pelletier 1995).  The challenge lies in specifying a mapping from surface structure to such a logical form. While many of the principles underlying the ambiguities illustrated above are reasonably well understood, general interpretive algorithms are still lacking. It appears that such algorithms will involve stepwise elaboration of an initially incomplete, ambiguous logical form, rather than a straightforward syntax-semantics transduction, since the features on which the correct formalization depends transcend syntax: They include ones such as Carlson's individual-level/stage-level distinction among verb phrases and his object-level/kind-level distinction among verb arguments (Carlson 1977, 1982), as well as pragmatic features such as the given/new distinction (influenced by phrasal accent), lexical presuppositions, linguistic context, and background knowledge.