  Lexicon acquisition from machine-readable dictionaries and corpora is
currently a dynamic field of research, yet it is often not clear how lexical
information so acquired can be used, or how it relates to structured meaning
representations. In this paper I look at this issue in relation to Information
Extraction (hereafter IE), and one subtask for which both lexical and general
knowledge are required, Word Sense Disambiguation (WSD). The analysis is based
on the widely-used, but little-discussed distinction between an IE system's
foreground lexicon, containing the domain's key terms which map onto the
database fields of the output formalism, and the background lexicon, containing
the remainder of the vocabulary. For the foreground lexicon, human lexicography
is required. For the background lexicon, automatic acquisition is appropriate.
  For the foreground lexicon, WSD will occur as a by-product of finding a
coherent semantic interpretation of the input. WSD techniques as discussed in
recent literature are suited only to the background lexicon. Once the
foreground/background distinction is developed, there is a match between what
is possible, given the state of the art in WSD, and what is required, for
high-quality IE.
