To address the second challenge, and to make conversion into high-quality TEI-XML encoded corpora feasible, we ignored PDF ebooks and limited our focus to the 273,976 books available in the XML-based EPUB format and drew a 10% random sample from these as a first step, stratified by year of publication, resulting in a sample of 26,091 ebooks. As a second step, on the occasion of the 20th anniversary of the German Book Prize in October 2024, we added all 362 digitally available longlisted titles from the past two decades to the corpus, in cooperation with the German Publishers and Booksellers Association. To convert the data to the TEI I5 format (Lüngen and Sperberg-McQueen 2012) used by DeReKo, we applied XSLT 3.0 stylesheets in three passes, via the Saxon XSLT processor and GNU Make, using the DNB SRU API to retrieve consistent metadata, a heuristic genre classifier based on this, and a MALLET (McCallum 2002) based implementation of the standard DeReKo topic domain classifier (Weiß 2005; Klosa, Lüngen, and Kupietz 2012). In subsequent steps, the TEI-XML data was converted to KorAP-XML format and annotated for POS and lemma using the TreeTagger (Schmid 1994), for POS and morphosyntactic properties using MarMoT (Mueller et al. 2013), and dependencies using MaltParser (Nivre et al. 2007). These tools were selected due to their good balance between accuracy and performance. <hi xmlns="http://www.tei-c.org/ns/1.0" rend="sup"><ref n="2" target="ftn2" /> </hi> If required for specific applications, additional annotation layers can be added later, since KorAP supports any number of them. <hi xmlns="http://www.tei-c.org/ns/1.0" rend="sup"><ref n="3" target="ftn3" /> </hi>