Dating of medieval text sources is a central task common to the field of manuscript studies. It is a difficult process requiring expert philological and historical knowledge. We investigate the issue of automatic dating of a collection of about 300 charters from medieval Denmark, in particular how n-gram models based on different transcription levels of the charters can be used to assign the manuscripts to a specific temporal interval. We frame the problem as a classification task by dividing the period into bins of 50 years and using these as classes in a supervised learning setting to develop SVM classifiers. We show that the more detailed facsimile transcription, which captures palaeographic characteristics of a text, provides better results than the diplomatic level, where such distinctions are normalised. Furthermore, both character and word n-grams show promising results, the highest accuracy reaching 74.96 %. This level of classification accuracy corresponds to being able to date almost 75 % of the charters with a 25-year error margin, which philologists use as a standard of the precision with which medieval texts can be dated manually.peer-reviewe
