If we look at a data model, is a definition of an entity type automatically produced by listing the attributes of the entity type? If this were true then a data modeler would not need to produce entity definitions - he or she would simply need to identify and list a sufficient number of attributes. I have actually heard data modelers being criticized by terminologists for doing just this. The extent to which such criticism is fair or not is a separate discussion, but the question remains as to whether a list of attributes can suffice as a definition.
I do not think that a list of attributes is sufficient based on the recent discussions about concept systems in this blog. No concept exists in isolation. Every concept exists in some kind of concept system where it has relationships to other concepts. At least some of these relationships and/or related concepts have to enter into a definition so that the concept being defined can be located properly in a concept system, which appears to be necessary for knowledge.
A list of attributes usually will not distinguish between those that are determining for the concept under consideration, and those which are not - some of which may be shared with other concepts. Thus, just reviewing a list of attributes becomes a test of figuring out which ones are pertinent to a definition. This surely defeats the practical aspects of definition.
It would seem therefore that something more than a list of attributes is required to produce a quality definition. While many data modelers do produce quality definitions, it can be seen that the practice of data modeling may present the temptation to just assume that the definition of an entity type is provided by the attributes captured for it. Of course, relationships and other concepts are present in a data model, but it will need another blog to answer the question of whether a data model has enough information to produce a definition based on entity types, attributes, and relationships alone.