  Natural language understanding applications such as interactive planning and
face-to-face translation require extensive inferencing. Many of these
inferences are based on the meaning of particular open class words. Providing a
representation that can support such lexically-based inferences is a primary
concern of lexical semantics. The representation language of first order logic
has well-understood semantics and a multitude of inferencing systems have been
implemented for it. Thus it is a prime candidate to serve as a lexical
semantics representation. However, we argue that FOL, although a good starting
point, needs to be extended before it can efficiently and concisely support all
the lexically-based inferences needed.
