Designed about ten years ago, the \textsc{Terminae} method and workbench for ontology engineering from texts have been going on evolving since then. Our investigations integrate the experience gained through its use in industrial and academic projects, the progress of natural language processing as well as the evolution of the ontology engineering. Several new methodological guidelines, such as the reuse of core ontologies, have been added to the method and implemented in the workbench. It has also been modified in order to be compliant to some recent standards such as the OWL knowledge representation. The paper recalls the terminology engineering principles underlying Terminae and comments its originality. Then it presents the kind of conceptual model that is built with this method, and their knowledge representation. The method and the support provided by the workbench are detailed and illustrated with a case-study in law. With regard to the state of the art, \textsc{Terminae} is one of the most supervised methods in the trend of ontology learning. This option raises epistemological issues about how language and knowledge can be articulated and the distance that separate formal ontologies from learning conceptual models.