This paper introduces association norms of German noun compounds as a lexical-semantic resource for cognitive and computational linguistics research on compositionality. Based on an existing database of German noun compounds, we collected human associations to the compounds and their constituents within a web experiment. The current study describes the collection process and a part-of-speech analysis of the association resource. In addition, we demonstrate that the associations provide insight into the semantic properties of the compounds, and perform a case study that predicts the degree of compositionality of the experiment compound nouns, as relying on the norms. Applying a comparatively simple measure of association overlap, we reach a Spearman rank correlation coefficient of rs = 0.5228, p <.000001, when comparing our predictions with human judgements.
Participants were presented with the written instructions for the experiment and an example item with potential responses. In the actual experiment, each trial consisted of a single word presented in a box at the top of the screen.