  This paper describes how the current lexical similarity and analogy gold
standards are built to conform to certain ideas about what the models they are
designed to evaluate are used for. Topical relevance has always been the most
important target notion for information access tools and related language
technology technologies, and while this has proven a useful starting point for
much of what information technology is used for, it does not always align well
with other uses to which technologies are being put, most notably use cases
from digital scholarship in the humanities or social sciences. This paper
argues for more systematic formulation of requirements from the digital
humanities and social sciences and more explicit description of the assumptions
underlying model design.
