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Mock fiction is a genre of humorous, fictional narratives. It is pervasive in adolescents’ peer-group interaction. Building on a corpus of informal peer-group interaction among 14 to 17 year-old German adolescents, it is shown how mock fiction is used to sanction identity-claims of peer-group co-members that are taken to be inadequate by the teller of a mock fiction. Mock fiction exposes and ridicules those claims by fictional exaggeration. Mock fiction is an indirect, yet sometimes even highly abusive means for criticizing and negotiating identities and statuses of peer-group members. The analysis shows how mock fiction is collaboratively produced, how it is used to convey criticism and to negotiate social norms indirectly, and how, in addition, it allows for performative self-positioning of the tellers as skilled, entertaining tellers and socio-psychological diagnosticians.
Question Answering Systems for retrieving information from Knowledge Graphs (KG) have become a major area of interest in recent years. Current systems search for words and entities but cannot search for grammatical phenomena. The purpose of this paper is to present our research on developing a QA System that answers natural language questions about German grammar.
Our goal is to build a KG which contains facts and rules about German grammar, and is also able to answer specific questions about a concrete grammatical issue. An overview of the current research in the topic of QA systems and ontology design is given and we show how we plan to construct the KG by integrating the data in the grammatical information system Grammis, hosted by the Leibniz-Institut für Deutsche Sprache (IDS). In this paper, we describe the construction of the initial KG, sketch our resulting graph, and demonstrate the effectiveness of such an approach. A grammar correction component will be part of a later stage. The paper concludes with the potential areas for future research.
Terminological resources play a central role in the organization and retrieval of scientific texts. Both simple keyword lists and advanced modelings of relationships between terminological concepts can make a most valuable contribution to the analysis, classification, and finding of appropriate digital documents, either on the web or within local repositories. This seems especially true for long-established scientific fields with elusive theoretical and historical branches, where the use of terminology within documents from different origins is often far from being consistent. In this paper, we report on the progress of a linguistically motivated project on the onomasiological re-modeling of the terminological resources for the grammatical information system grammis. We present the design principles and the results of their application. In particular, we focus on new features for the authoring backend and discuss how these innovations help to evaluate existing, loosely structured terminological content, as well as to efficiently deal with automatic term extraction. Furthermore, we introduce a transformation to a future SKOS representation. We conclude with a positioning of our resources with regard to the Knowledge Organization discourse and discuss how a highly complex information environment like grammis benefits from the re-designed terminological KOS.
The lexicography of German
(2020)
This chapter discusses the main dictionaries of the German language as it is spoken and written in Germany, and also German as it is spoken and written in Austria, Switzerland, the eastern fringes of Belgium, and South Tyrol. It also briefly describes Pennsylvania German. Corpora and other language resources used in German dictionary-making are also presented. Finally, there is a discussion of some current issues in German lexicography, as well as future prospects.
We present a method to identify and document a phenomenon on which there is very little empirical data: German phrasal compounds occurring in the form of as a single token (without punctuation between their components). Relying on linguistic criteria, our approach implies to have an operational notion of compounds which can be systematically applied as well as (web) corpora which are large and diverse enough to contain rarely seen phenomena. The method is based on word segmentation and morphological analysis, it takes advantage of a data-driven learning process. Our results show that coarse-grained identification of phrasal compounds is best performed with empirical data, whereas fine-grained detection could be improved with a combination of rule-based and frequency-based word lists. Along with the characteristics of web texts, the orthographic realizations seem to be linked to the degree of expressivity.