The problem of deciding what was implied by a written text, of ‘‘reading between the lines’ ’ isthe problem of inference. Toextract proper inferences from a text requires a great deal of general knowledge on the part of the reader. Past approaches have often postulated an algorithm tuned to process a particular kind of knowledge structure (such as ascript, or a plan). An alternative, unified approach is proposed. The algorithm recognizes six very general classes of inference, classes that are not dependent on individual knowledge structures, but instead rely on patterns of connectivity between concepts. The complexity has been effectively shifted from the algorithm to the knowledge base; new kinds of knowledge structures can be added without modifying the algorithm. 1. The Problem of Inferencing The reader of a text is faced with a formidable task: recognizing the individual words of the text, deciding how they are structured into sentences, determining the explicit meaning of each sentence, and also making inferences about the likely implicit meaning of each sentence, and the implicit connections between sentences. An inference is defined to be any assertion which the reader