Korpuslinguistik
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For many reasons, Mennonite Low German is a language whose documentation and investigation is of great importance for linguistics. To date, most research projects that deal with this language and/ or its speakers have had a relatively narrow focus, with many of the data cited being of limited relevance beyond the projects for which they were collected. In order to create a resource for a broad range of researchers, especially those working on Mennonite Low German, the dataset presented here has been transformed into a structured and searchable corpus that is accessible online. The translations of 46 English, Spanish, or Portuguese stimulus sentences into Mennonite Low German by 321 consultants form the core of the MEND-corpus (Mennonite Low German in North and South America) in the Archive for Spoken German. In addition to describing the origin of this corpus and discussing possibilities and limitations for further research, we discuss the technical structure and search possibilities of the Database for Spoken German. Among other things, this database allows for a structured search of metadata, a context-sensitive token search, and the generation of virtual corpora that can be shared with others. Moreover, thanks to its text-sound alignment, one can easily switch from a particular text section of the corpus to the corresponding audio section. Aside from the desire to equip the reader with the technical knowledge necessary to use this corpus, a further goal of this paper is to demonstrate that the corpus still offers many possibilities for future research.
This paper presents an extended annotation and analysis of interpretative reply relations focusing on a comparison of reply relation types and targets between conflictual pages and neutral pages of German Wikipedia (WP) talk pages. We briefly present the different categories identified for interpretative reply relations to analyze the relationship between WP postings as well as linguistic cues for each category. We investigate referencing strategies of WP authors in discussion page postings, illustrated by means of reply relation types and targets taking into account the degree of disagreement displayed on a WP talk page. We provide richly annotated data that can be used for further analyses such as the identification of interactional relations on higher levels, or for training tasks in machine learning algorithms.
Der Umgang mit längeren, komplexeren Redebeiträgen hat als Gegenstand der Mündlichkeitsdidaktik in Sprachvermittlung sowie Sprachbildung viel Aufmerksamkeit erfahren. Empirische Untersuchungen dazu, in welchen Sprachverwendungskontexten lange Redebeiträge in natürlichen Gesprächssituationen häufig vorkommen und damit die Fähigkeit, sie verstehen und produzieren zu können, eine Anforderung für Lernende bildet, stehen jedoch noch aus. Der Beitrag stellt eine explorative Studie auf der Basis des Forschungs- und Lehrkorpus Gesprochenes Deutsch (FOLK) vor, die zeigt, wie durch korpuslinguistische Analysen anhand von Interaktionskorpora eine Beschreibung der Gebrauchsspezifika langer Redebeiträge für ein weites Spektrum an Gesprächskontexten gewonnen und damit eine Grundlage für die zielgruppenspezifische Vermittlung diskursiver Fähigkeiten im DaF/DaZ-Unterricht bereitgestellt werden kann.
In this article, we examine the current situation of data dissemination and provision for CMC corpora. By that we aim to give a guiding grid for future projects that will improve the transparency and replicability of research results as well as the reusability of the created resources. Based on the FAIR guiding principles for research data management, we evaluate the 20 European CMC corpora listed in the CLARIN CMC Resource family, individuate successful strategies among the existing corpora and establish best practices for future projects. We give an overview of existing approaches to data referencing, dissemination and provision in European CMC corpora, and discuss the methods, formats and strategies used. Furthermore, we discuss the need for community standards and offer recommendations for best practices when creating a new CMC corpus.
Dieser Beitrag beschreibt die Motivation und Ziele hinter der Initiative Europäisches Referenzkorpus EuReCo. Ausgehend von den Desiderata, die sich aufgrund der Defizite verfügbarer Forschungsdaten wie monolinguale Korpora, Parallelkorpora und Vergleichskorpora für den Sprachvergleich ergeben, werden die bisherigen und die laufenden Arbeiten im Rahmen von EuReCo präsentiert und anhand vergleichender deutsch-rumänischer Kookkurrenzanalysen neue Perspektiven für kontrastive Korpuslinguistik, die die EuReCo-Initiative öffnet, skizziert.
Kontrastive Korpuslinguistik versteht sich als eine Bezeichnung für sprachvergleichende Studien, deren Ergebnisse mit Analysen sprachlicher Daten erreicht und empirisch fundiert sind. Die Bezeichnung contrastive corpus linguistics für eine neue, sich entwickelnde Disziplin wurde 1996 von Karin Aijmer und Bengt Altenberg (Schmied 2009: 1142) eingeführt. Der Einsatz der sprachlichen Korpora bei der Beschreibung kontrastiver Studien bedeutet in den 1990er-Jahren für die kontrastive Linguistik eine Wiederbelebung, nachdem die weit gesteckten Ziele und Hoffnungen in den 50er- und 60er-Jahren, die mit der Fremdsprachendidaktik zusammenhingen, vor etwa 50 Jahren aufgegeben wurden.
Kontrastive Korpuslinguistik
(2022)
This paper describes a method for extracting collocation data from text corpora based on a formal definition of syntactic structures, which takes into account not only the POS-tagging level of annotation but also syntactic parsing (syntactic treebank model) and introduces the possibility of controlling the canonical form of extracted collocations based on statistical data on forms with different properties in the corpus. Specifically, we describe the results of extraction from the syntactically tagged Gigafida 2.1 corpus. Using the new method, 4,002,918 collocation candidates in 81 syntactic structures were extracted. We evaluate the extracted data sample in more detail, mainly in relation to properties that affect the extraction of canonical forms: definiteness in adjectival collocations, grammatical number in noun collocations, comparison in adjectival and adverbial collocations, and letter case (uppercase and lowercase) in canonical forms. The conclusion highlights the potential of the methodology used for the grammatical description of collocation and phrasal syntax and the possibilities for improving the model in the process of compilation of a digital dictionary database for Slovene.
When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state of the art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.
Enabling appropriate access to linguistic research data, both for many researchers and for innovative research applications, is a challenging task. In this chapter, we describe how we address this challenge in the context of the German Reference Corpus DeReKo and the corpus analysis platform KorAP. The core of our approach, which is based on and tightly integrated into the CLARIN infrastructure, is to offer access at different levels. The graduated access levels make it possible to find a low-loss compromise between the possibilities opened up and the costs incurred by users and providers for each individual use case, so that, viewed over many applications, the ratio between effort and results achieved can be effectively optimized. We also report on experiences with the current state of this approach.