12. A machine for automatically extracting a conceptual graph, comprising: a microprocessor or processor coupled to a memory, wherein the microprocessor or processor is programmed to extract a conceptual graph from a text by: first determining a set of pedagogically significant key terms, wherein the key terms are derived from text that does not include the text from which the conceptual graphs are generated; subsequently obtaining a set of pre-determined semantic relations between the pedagogically significant key terms based on a particular subject matter area or domain, and according to a prescribed set of edge relations; subsequently obtaining parse output by semantically parsing one or more text files in computer-readable form related to the subject matter area or domain; and after semantically parsing the one or more text files, deriving semantic relations between terms in the parse output according to the set of pre-determined semantic relations between the pedagogically significant key terms based on the subject matter area or domain, and according to the prescribed set of edge relations; further wherein the microprocessor processor is programmed to create one or more questions in an automated tutor system from said conceptual graph.
12. A machine for automatically extracting a conceptual graph, comprising: a microprocessor or processor coupled to a memory, wherein the microprocessor or processor is programmed to extract a conceptual graph from a text by: first determining a set of pedagogically significant key terms, wherein the key terms are derived from text that does not include the text from which the conceptual graphs are generated; subsequently obtaining a set of pre-determined semantic relations between the pedagogically significant key terms based on a particular subject matter area or domain, and according to a prescribed set of edge relations; subsequently obtaining parse output by semantically parsing one or more text files in computer-readable form related to the subject matter area or domain; and after semantically parsing the one or more text files, deriving semantic relations between terms in the parse output according to the set of pre-determined semantic relations between the pedagogically significant key terms based on the subject matter area or domain, and according to the prescribed set of edge relations; further wherein the microprocessor processor is programmed to create one or more questions in an automated tutor system from said conceptual graph. 16. The machine of claim 12 , wherein the set of pre-determined semantic relations is based on specific relations between key terms for the subject matter area or domain, and on psychologically-motivated general relations.