Because of the results from the previous section, we decided to modify our task to a word-level prediction, which enables us to include more context by ignoring sentence boundaries and at the same time make more fine-grained predictions. In this second classification task, each word is to be classified separately as inside or outside a direct speech. As baseline for this task, we trained a Linear Chain Conditional Random Field (CRF) that was only given the word itself and its part-of-speech tag. This CRF stagnated at a comparably low accuracy of 0 <hi xmlns="http://www.tei-c.org/ns/1.0" rend="bold">.71</hi> using cross-validation on the <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">Kerncorpus</hi>.