In this paper we explain the difference between two aspects of semantic relatedness: taxonomic and thematic relations. We notice the lack of evaluation tools for measuring thematic relatedness, identify two datasets that can be recommended as thematic benchmarks, and verify them experimentally. In further experiments, we use these datasets to perform a comprehensive analysis of the performance of an extensive sample of computational models of semantic relatedness, classified according to the sources of information they exploit. We report models that are best at each of the two dimensions of semantic relatedness and those that achieve a good balance between the two.