We describe a new GATE-based linguistic annotation pipeline for Early Modern German, which can be used to annotate historical texts with word tokens, sentence boundaries, lemmas, and POS tags. The pipeline is based on a customisation of the freely available ANNIE system for English (Cunningham et al., 2002), in combination with a version of the TreeTagger (Schmid, 1994) trained on gold standard Early Modern German data. The POS-tagging and lemmatisation components of the pipeline achieve an average accuracy of 89.44% and 83.16%, respectively, on unseen historical data from various genres and publication dates within the Early Modern period. We show that normalisation of spelling variation can further improve these results. With no specialised tools available for processing this particular stage of the language, this pipeline will be of particular interest to smaller, humanities-based projects wishing to add linguistic annotations to their historical data but which lack the means or resources to develop such tools themselves.

This paper describes a three-part annotation scheme for superlatives. The first identifies syntactic classes, since superlatives can serve different semantic purposes. The second and third only apply to superlatives that express straight-forward comparisons between targets and their comparison sets. The second form of annotation identifies the spans of each target and comparison set, which is of interest for relation extraction. The third form labels superlatives as facts or opinions, which has not yet been undertaken in the area of sentiment detection. The annotation scheme has been tested and evaluated on 500 tokens of superlatives, the results of which are presented in Section 5. In addition to providing a platform for investigating superlatives on a larger scale, this research also introduces a new text-based Wikipedia corpus which is especially suitable for linguistic research.