We describe WHIRL, an "information representation language" that synergisti
cally combines properties of logic-based and text-based representation syst
ems. WHIRL is a subset of Datalog that has been extended by introducing an
atomic type for textual entities, an atomic operation for computing textual
similarity, and a "soft" semantics; that is, inferences in WHIRL are assoc
iated with numeric scores, and presented to the user in decreasing order by
score. This paper briefly describes WHIRL, and then surveys a number of ap
plications. We show that WHIRL strictly generalizes both ranked retrieval o
f documents, and logical deduction; that nontrivial queries about large dat
abases can be answered efficiently; that WHIRL can be used to accurately in
tegrate data from heterogeneous information sources, such as those found on
the Web; that WHIRL can be used effectively for inductive classification o
f text; and finally, that WHIRL can be used to semi-automatically generate
extraction programs for structured documents. (C) 2000 Published by Elsevie
r Science B.V. All rights reserved.