  This paper describes an algorithm for the computation of FIRST and FOLLOW
sets for use with feature-theoretic grammars in which the value of the sets
consists of pairs of feature-theoretic categories. The algorithm preserves as
much information from the grammars as possible, using negative restriction to
define equivalence classes. Addition of a simple data structure leads to an
order of magnitude improvement in execution time over a naive implementation.
