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This paper addresses the troublesome question of feature selection and content prediction in definition writing. I present the basis of definition-authoring tools that can be used across a range of contexts, independently of the domain and language of the definitions. In addition to being domain- and language-independent, these tools should be easily tailorable to specific domains. Thus, my work seeks to contribute to developing generic definition-writing aids that can be tailored to a range of different contexts and domains. The objectives of this article are: (1) to show that it is possible to create implementable generic definition models; (2) to show how to constrain these models to produce definitions relevant to particular contexts; and (3) to propose an ontological analysis framework with a fixed and well-motivated descriptive vocabulary that can be used in further content analysis studies in terminology and to enhance integration of textual definitions in ontologies.