  Word meaning is notoriously difficult to capture, both synchronically and
diachronically. In this paper, we describe the creation of the largest resource
of graded contextualized, diachronic word meaning annotation in four different
languages, based on 100,000 human semantic proximity judgments. We thoroughly
describe the multi-round incremental annotation process, the choice for a
clustering algorithm to group usages into senses, and possible - diachronic and
synchronic - uses for this dataset.
