Refine
Year of publication
Document Type
- Part of a Book (1761)
- Article (1167)
- Conference Proceeding (442)
- Book (217)
- Other (101)
- Review (61)
- Working Paper (47)
- Part of Periodical (29)
- Doctoral Thesis (25)
- Report (17)
Language
- German (2836)
- English (960)
- French (22)
- Multiple languages (18)
- Russian (14)
- Spanish (11)
- Portuguese (9)
- Ukrainian (4)
- Latvian (3)
- Polish (3)
Keywords
- Deutsch (1506)
- Korpus <Linguistik> (543)
- Konversationsanalyse (208)
- Wörterbuch (178)
- Gesprochene Sprache (176)
- Grammatik (162)
- Interaktion (152)
- Sprachgebrauch (139)
- Kommunikation (138)
- Computerlinguistik (136)
Publicationstate
- Veröffentlichungsversion (3883) (remove)
Reviewstate
- (Verlags)-Lektorat (2491)
- Peer-Review (1007)
- Verlags-Lektorat (79)
- Peer-review (37)
- Qualifikationsarbeit (Dissertation, Habilitationsschrift) (33)
- Review-Status-unbekannt (12)
- Abschlussarbeit (Bachelor, Master, Diplom, Magister) (Bachelor, Master, Diss.) (5)
- (Verlags-)Lektorat (4)
- Verlagslektorat (4)
- Peer-Revied (3)
Publisher
- de Gruyter (619)
- Institut für Deutsche Sprache (354)
- Leibniz-Institut für Deutsche Sprache (IDS) (222)
- Narr (207)
- IDS-Verlag (108)
- Lang (97)
- Niemeyer (90)
- De Gruyter (59)
- Verlag für Gesprächsforschung (51)
- Association for Computational Linguistics (44)
We introduce DeReKoGram, a novel frequency dataset containing lemma and part-of-speech (POS) information for 1-, 2-, and 3-grams from the German Reference Corpus. The dataset contains information based on a corpus of 43.2 billion tokens and is divided into 16 parts based on 16 corpus folds. We describe how the dataset was created and structured. By evaluating the distribution over the 16 folds, we show that it is possible to work with a subset of the folds in many use cases (e.g., to save computational resources). In a case study, we investigate the growth of vocabulary (as well as the number of hapax legomena) as an increasing number of folds are included in the analysis. We cross-combine this with the various cleaning stages of the dataset. We also give some guidance in the form of Python, R, and Stata markdown scripts on how to work with the resource.
Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different aspects of human language. Here, we use LMs to test the hypothesis that languages with more speakers tend to be easier to learn. In two experiments, we train several LMs—ranging from very simple n-gram models to state-of-the-art deep neural networks—on written cross-linguistic corpus data covering 1293 different languages and statistically estimate learning difficulty. Using a variety of quantitative methods and machine learning techniques to account for phylogenetic relatedness and geographical proximity of languages, we show that there is robust evidence for a relationship between learning difficulty and speaker population size. However, contrary to expectations derived from previous research, our results suggest that languages with more speakers tend to be harder to learn.
Recent years have seen a growing interest in grammatical variation, a core explanandum of grammatical theory. The present volume explores questions that are fundamental to this line of research: First, the question of whether variation can always and completely be explained by intra- or extra-linguistic predictors, or whether there is a certain amount of unpredictable – or ‘free’ – grammatical variation. Second, the question of what implications the (in-)existence of free variation would hold for our theoretical models and the empirical study of grammar. The volume provides the first dedicated book-length treatment of this long-standing topic. Following an introductory chapter by the editors, it contains ten case studies on potentially free variation in morphology and syntax drawn from Germanic, Romance, Uralic and Mayan.
Allusion
(2023)
Assessment
(2023)
Most broadly, an assessment is a type of social action by which an interactant expresses an evaluative stance towards someone or something (e.g., an object, an event, an action, an experience, a state of affairs, a place, a circumstance, etc.). The target of an assessment is typically called the ‘assessable’.
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.
KoMuX, der Kompositamuster-Explorer, (www.owid.de/plus/komux) ist eine Webanwendung, die es ermöglicht, mehr als 50.000 nominale Komposita des Deutschen gezielt nach abstrakten oder lexikalisch-teilspezifizierten Mustern zu durchsuchen. Unterschiedliche Visualisierungen helfen dabei, Strukturen und Zusammenhänge innerhalb der Ergebnismenge zu erfassen.
Retro-sequence
(2023)