  Explanation-based generalization is used to extract a specialized grammar
from the original one using a training corpus of parse trees. This allows very
much faster parsing and gives a lower error rate, at the price of a small loss
in coverage. Previously, it has been necessary to specify the tree-cutting
criteria (or operationality criteria) manually; here they are derived
automatically from the training set and the desired coverage of the specialized
grammar. This is done by assigning an entropy value to each node in the parse
trees and cutting in the nodes with sufficiently high entropy values.
