In terms of domain, <cite>Barzilay and Elhadad (2003)</cite> used city descriptions from an encyclopedia for their experiments. For these descriptions clustering worked well because all articles had the same structure (paragraphs about culture, sports, etc.). The domain of our corpus was broader: It included information about housing, work, and events for people with disabilities as well as information about the organizations behind the respective websites. Apart from language and domain challenges we observed heavy transformations from AS to LS in our data (Figure 1 shows a sample article in AS and LS). As a result, LS paragraphs were typically very short and the clustering process returned many singleton clusters.