This empirical research project investigates the language elaboration of Middle Low German from the 13th century to the written language shift in the 16th/17th century. At this time, Middle Low German lost its dominant position as a supraregional written language to Early New High German. This study makes an important contribution to the reconstruction of grammatical developments in written Middle Low German as historical written language, which are hitherto examined only to some extent. The investigation focuses on urban legal statutes for which there are several reasons: Processes of language elaboration are most likely found first in legal statutes as those need to construe complex (legal) issues understandable independently of contextual information. These legal issues specifically occur in the form of conditional relations; consequently, we are able to examine changes concerning the linguistic construction of conditionality during the investigation period. Furthermore, legal statutes are locatable and dateable, with the result that developmental dynamics of elaboration processes can be spatio-temporally reconstructed.
We are developing an interactive procedure that combines machine learning and expert feedback to solve one of the most central problems of existing annotation tools for historical texts. Existing parsing and tagging systems require static grammars and grammatical categories but these are of no use due to the historical dynamics of grammar. We want to discover an evolving, dynamic grammar by using rule-based text analysis techniques and machine learning methods. This enables us to reconstruct the language elaboration in an evidence-based way, which is a novelty. This requires knowledge about historical language and grammar as well as knowledge about computational linguistics and computer science. Therefore, this project is an interdisciplinary one that requires a close cooperation over the whole funding period.