  We study the notion of hierarchy in the context of visualizing textual data
and navigating text collections. A formal framework for ``hierarchy'' is given
by an ultrametric topology. This provides us with a theoretical foundation for
concept hierarchy creation. A major objective is {\em scalable} annotation or
labeling of concept maps. Serendipitously we pursue other objectives such as
deriving common word pair (and triplet) phrases, i.e., word 2- and 3-grams. We
evaluate our approach using (i) a collection of texts, (ii) a single text
subdivided into successive parts (for which we provide an interactive
demonstrator), and (iii) a text subdivided at the sentence or line level. While
detailing a generic framework, a distinguishing feature of our work is that we
focus on {\em locality} of hierarchic structure in order to extract semantic
information.
