However, such limited, specialized inference methods fall far short of the kind of general reasoning based on symbolic knowledge that has long been the goal in AI question answering. One of the earliest efforts to create a truly inferential QA system was the ENGLAW project of L. Stephen Coles (Coles 1972). ENGLAW was intended as a prototype of a kind of system that might be used by scientists and engineers to obtain information about physical laws. It featured a KB of axioms (in first-order logic) for 128 important physical laws, manually coded with the aid of a reference text. Questions (such as “In the Peltier Effect, does the heat developed depend on the direction of the electric current?”) were rendered into logic via a transformational grammar parser, and productions (aided by various Lisp functions) that map phrase patterns to logical expressions. The system was not developed to the point of practical usefulness, but its integration of reasoning and NLP technologies and its methods of selectively retrieving axioms for inferential QA were noteworthy contributions.