Knowledge-based acquisition of causal relationships in text

Abstract In this paper, we describe a procedure that integrates several techniques for recognizing causal relationships in expository text. Applying these techniques yields a knowledge representation consisting of classifications of the causal relationships contained in a text. This procedure is very robust. If any one of the techniques for recognizing a causal relationship fails, an alternate methodology can be used to continue the causal analysis. The procedure we will describe is embodied in a program called the causal analyser. We have applied the causal analyser to several texts to produce a representation of the causal relationships in these texts. The causal analyser described in this paper will be part of a knowledge acquisition system called TAKT (tool for the acquisition of knowledge from text), which is currently being developed.