WHIRL: A word-based information representation language

We describe WHIRL, an \information representation language" that synergistically combines properties of logic-based and text-based representation systems. WHIRL is a subset of non-recursive 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 associated with numeric scores, and presented to the user in decreasing order by score. We show that WHIRL strictly generalizes both ranked retrieval of documents, and logical deduction; that non-trivial queries about large databases can be answered eeciently; that WHIRL can be used to accurately integrate data from heterogeneous information sources, such as those found on the Web; that WHIRL can be used eeectively for inductive classiication of text; and nally, that WHIRL can be used to semi-automatically generate extraction programs for structured documents.