Refine
Year of publication
Document Type
- Article (117)
- Part of a Book (117)
- Conference Proceeding (107)
- Book (25)
- Working Paper (10)
- Other (9)
- Preprint (7)
- Part of Periodical (4)
- Doctoral Thesis (2)
- Course Material (1)
Language
- English (402) (remove)
Is part of the Bibliography
- yes (402) (remove)
Keywords
- Korpus <Linguistik> (131)
- Deutsch (115)
- Interaktion (46)
- Konversationsanalyse (36)
- Computerlinguistik (33)
- Forschungsdaten (32)
- Gesprochene Sprache (31)
- Annotation (26)
- Englisch (22)
- Online-Wörterbuch (21)
Publicationstate
- Veröffentlichungsversion (402) (remove)
Reviewstate
Publisher
- IDS-Verlag (34)
- de Gruyter (22)
- European Language Resources Association (ELRA) (16)
- Linköping University Electronic Press (14)
- European language resources association (ELRA) (13)
- Lexical Computing CZ s.r.o. (12)
- Springer (12)
- Association for Computational Linguistics (11)
- Springer Nature (10)
- The Association for Computational Linguistics (10)
The annual microcensus provides Germany’s most important official statistics. Unlike a census it does not cover the whole population, but a representative 1%-sample of it. In 2017, the German microcensus asked a question on the language of the population, i.e. ‘Which language is mainly spoken in your household?’ Unfortunately, the question, its design and its position within the whole microcensus’ questionnaire feature several shortcomings. The main shortcoming is that multilingual repertoires cannot be captured by it. Recommendations for the improvement of the microcensus’ language question: first and foremost the question (i.e. its wording, design, and answer options) should make it possible to count multilingual repertoires.
This paper explores how attitudes affect the seemingly objective process of counting speakers of varieties using the example of Low German, Germany’s sole regional language. The initial focus is on the basic taxonomy of classifying a variety as a language or a dialect. Three representative surveys then provide data for the analysis: the Germany Survey 2008, the Northern Germany Survey 2016, and the Germany Survey 2017. The results of these surveys indicate that there is no consensus concerning the evaluation of Low German’s status and that attitudes towards Low German are related to, for example, proficiency in the language. These attitudes are shown to matter when counting speakers of Low German and investigating the status it has been accorded.
Who understands Low German today and who can speak it? Who makes use of media and cultural events in Low German? What images do people in northern Germany associate with Low German and what is their view of their regional language?
These and further questions are answered in this brochure with the help of representative data collected in a telephone survey of a total of 1,632 people from eight federal states (Bremen, Hamburg, Lower Saxony, Mecklenburg-West Pomerania and Schleswig-Holstein as well as Brandenburg, North Rhine-Westphalia and Saxony-Anhalt).
This White Paper sets out commonly agreed definitions on activities of consortia within NFDI. It aims to provide a common basis for reporting and reference regarding selected questions of cross-consortial relevance in DFG’s template for the Interim Reports. The questions were prioritised by an NFDI Task Force on Evaluation and Reporting (formerly Task Force Monitoring) as a result of discussing possible answers to the DFG template. In this process the need to agree on a generalizable meaning of terms commonly used in the context of NFDI, and reporting in particular, were identified from cross-consortial perspectives. Questions that showed the highest requirement on clarification are discussed in this White Paper. As NFDI evolves, the Task Force will likely propose further joint approaches for reporting in information infrastructures.
While each of broad relevance, the questions addressed relate to substantially different aspects of consortia’s work. They are thus also structured slightly different.
Collaborative work in NFDI
(2023)
The non-profit association National Research Data Infrastructure (NFDI) promotes science and research through a National Research Data Infrastructure. Its aim is to develop and establish an overarching research data management (RDM) for Germany and to increase the efficiency of the entire German science system. After a two-and-a-half year build up phase, the process of adding new consortia, each representing a different data domain, has ended in March 2023. NFDI now has 26 disciplinary consortia (and one additional basic service collaboration). Now the full extent of cross-consortial interaction is beginning to show.
The automatic recognition of idioms poses a challenging problem for NLP applications. Whereas native speakers can intuitively handle multiword expressions whose compositional meanings are hard to trace back to individual word semantics, there is still ample scope for improvement regarding computational approaches. We assume that idiomatic constructions can be characterized by gradual intensities of semantic non-compositionality, formal fixedness, and unusual usage context, and introduce a number of measures for these characteristics, comprising count-based and predictive collocation measures together with measures of context (un)similarity. We evaluate our approach on a manually labelled gold standard, derived from a corpus of German pop lyrics. To this end, we apply a Random Forest classifier to analyze the individual contribution of features for automatically detecting idioms, and study the trade-off between recall and precision. Finally, we evaluate the classifier on an independent dataset of idioms extracted from a list of Wikipedia idioms, achieving state-of-the art accuracy.
In order to differentiate between figurative and literal usage of verb-noun combinations for the shared task on the disambiguation of German Verbal Idioms issued for KONVENS 2021, we apply and extend an approach originally developed for detecting idioms in a dataset consisting of random ngram samples. The classification is done by implementing a rather shallow, statistics-based pipeline without intensive preprocessing and examinations on the morphosyntactic and semantic level. We describe the overall approach, the differences between the original dataset and the dataset of the KONVENS task, provide experimental classification results, and analyse the individual contributions of our feature sets.
This poster summarizes the results of the CLARIAH-DE Work Package 3: Skills Training and Promotion of Junior Researchers.
For a research field that is characterised by rapid technical development, CLARIAH-DE has to include the promotion of data literacy necessary for the efficient use of this digital research infrastructure as part of its objective. To develop, consolidate and refine a common programme in this area, work package 3 set itself the following sub goals:
- Consolidation of the activities from the previous projects into a joint service
- Cataloguing and reflecting on the methods and tools used in the research field, with the aim of identifying remaining gaps
- Skills training of, individual support for and the promotion of junior researchers