The paper describes the foundations of a methodology for natural language-based knowledge acquisition. It concentrates on a special type of context: the case in which an analyst interviews an informant who is a domain expert and the text of the discussion is carefully recorded. In this context the following paradox arises: the analyst is after knowledge, but all he gets are words. Matching concepts to the words---or, more precisely, constructing conceptual structures which model the mental models of the informant---is the task of the analyst. The conceptual structures are to be specified as sets of conceptual graphs.
To carry out this task, the clear specification of the domain of discourse in terms of an ontology and an inventory becomes necessary. The discourse is considered to include not only the text of the discussion between the analyst and the informant, but also the ever-changing mental models of both parties. The mental models are construed as modelling some object domain ``out there'', but the domain of discourse is created through discourse.
A step-by-step technique is given for specifying the domain of discourse with careful attention paid to version control. It is noted that different interviews about the ``same'' object domain may give rise to several different domains of discourse.
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