SORTAL is a software assistant for performing meaning-triangle-based sortal analysis. This paper describes its architecture and possible implementations. Conceptual analysis and conceptual modelling are central components of the informant-and-analyst-based, natural language-mediated knowledge acquisition process, but focusing on concepts is not enough. The ``aboutness'' of the language used in the interview forces the analyst to recognize distinctions between words, concepts, referents, and cogniting agents. Creating frame-like representations for agent-centred meaning triangles, as well as updating ontologies, keeping track of multiple domains of discourse, and the creation of knowledge bases for use in other systems are tasks that can be assisted by a software tool such as SORTAL. We sketch the requirements for such an assistant, give examples of its operation, and address implementation issues.
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