This paper deals with the automatic discrimination of contexts of Czech ambiguous words. The Schutze's methodology was used, modified and transformed for the Czech language. This algorithm is based on vector space and clustering. The semantic discrimination could be understood as a subtask of word sense disambiguation. In this approach, the sense of word is defined as the cluster of contexts of ambiguous word. We show that Schutze's method is transportable into Czech. Our results are not as good as his because we have experimented with a highly ambiguous word.