Korpuslinguistik
Refine
Year of publication
Document Type
- Part of a Book (10)
- Article (7)
- Conference Proceeding (7)
- Other (1)
Has Fulltext
- yes (25)
Keywords
- Deutsches Referenzkorpus (DeReKo) (25) (remove)
Publicationstate
- Veröffentlichungsversion (12)
- Zweitveröffentlichung (6)
- Postprint (3)
Reviewstate
- (Verlags)-Lektorat (12)
- Peer-Review (7)
Publisher
- de Gruyter (6)
- Institut für Deutsche Sprache (4)
- European Language Resources Association (ELRA) (3)
- Narr (2)
- ELRA (1)
- German Society for Computational Linguistics & Language Technology (GSCL) (1)
- John Benjamins Publishing Company (1)
- Lancaster University (1)
- Leibniz-Institut für Deutsche Sprache (IDS) (1)
- University of Birmingham (1)
Für die spezifischen Bedürfnisse der Schreibbeobachtung wurde das Orthografische Kernkorpus (OKK) als virtuelles Korpus in DeReKo entwickelt. Mit derzeit rund 14 Mrd. Token deckt es den Schriftsprachgebrauch in den deutschsprachigen Ländern im Zeitraum von 1995 bis in die Gegenwart ab. Der Zugriff über die Korpusanalyseplattform KorAP erlaubt nicht nur die Nutzung verschiedener Annotationen, sondern über die API-Schnittstellen auch die Einbindung in diverse Auswertungsumgebungen wie RStudio über den RKorAPClient und macht es so für zahlreiche Analyse- und Visualisierungsmöglichkeiten zugänglich.
Das Deutsche Referenzkorpus DeReKo dient als eine empirische Grundlage für die germanistische Linguistik. In diesem Beitrag geben wir einen Überblick über Grundlagen und Neuigkeiten zu DeReKo und seine Verwendungsmöglichkeiten sowie einen Einblick in seine strategische Gesamtkonzeption, die zum Ziel hat, DeReKo trotz begrenzter Ressourcen für einerseits möglichst viele und andererseits auch für innovative und anspruchsvolle Anwendungen nutzbar zu machen. Insbesondere erläutern wir dabei Strategien zur Aufbereitung sehr großer Korpora mit notwendigerweise heuristischen Verfahren und Herausforderungen, die sich auf dem Weg zur linguistischen Erschließung solcher Korpora stellen.
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.
We present the use of count-based and predictive language models for exploring language use in the German Reference Corpus DeReKo. For collocation analysis along the syntagmatic axis we employ traditional association measures based on co-occurrence counts as well as predictive association measures derived from the output weights of skipgram word embeddings. For inspecting the semantic neighbourhood of words along the paradigmatic axis we visualize the high dimensional word embeddings in two dimensions using t-stochastic neighbourhood embeddings. Together, these visualizations provide a complementary, explorative approach to analysing very large corpora in addition to corpus querying. Moreover, we discuss count-based and predictive models w.r.t. scalability and maintainability in very large corpora.
In a recent article, Meylan and Griffiths (Meylan & Griffiths, 2021, henceforth, M&G) focus their attention on the significant methodological challenges that can arise when using large-scale linguistic corpora. To this end, M&G revisit a well-known result of Piantadosi, Tily, and Gibson (2011, henceforth, PT&G) who argue that average information content is a better predictor of word length than word frequency. We applaud M&G who conducted a very important study that should be read by any researcher interested in working with large-scale corpora. The fact that M&G mostly failed to find clear evidence in favor of PT&G's main finding motivated us to test PT&G's idea on a subset of the largest archive of German language texts designed for linguistic research, the German Reference Corpus consisting of ∼43 billion words. We only find very little support for the primary data point reported by PT&G.
In this paper, the basic assumptions are presented against the background of the development of a corpus-based method to determine suitable headword candidates for the LeGeDe-prototype (LeGeDe= Lexik des gesprochenen Deutsch), a lexicographical resource on spoken German. In a first quantitatively oriented step, potential one-word headword candidates are identified with the help of frequency class comparisons from a corpus for spoken (FOLK) and a subset from a corpus for written German (DEREKO). Qualitative analyses based on a project-specifically defined sample of data from the FOLK corpus lead to multi-word headword candidates. The results of the qualitative analyses were also compared with the results of studies from the research literature as well as (quantitative-orientated) bi- and trigram analyses. In their multi-word form, these candidates are particularly characterized by the fact that they assume a very special interactional function in the (authentic) interaction and have to be described as a whole unit. The paper explains this combined procedure, which was extracted in the LeGeDe-project for the appointment of headword candidates.
Der Beitrag beschreibt die Motivation und Ziele des Europäischen Referenzkorpus EuReCo, einer offenen Initiative, die darauf abzielt, dynamisch definierbare virtuelle vergleichbare Korpora auf der Grundlage bestehender nationaler, Referenz- oder anderer großer Korpora bereitzustellen und zu verwenden. Angesichts der bekannten Unzulänglichkeiten anderer Arten mehrsprachiger Korpora wie Parallel- bzw. Übersetzungskorpora oder rein webbasierte vergleichbare Korpora, stellt das EuReCo eine einzigartige linguistische Ressource dar, die neue Perspektiven für germanistische und vergleichende wie angewandte Korpuslinguistik, insbesondere im europäischen Kontext, eröffnet.
This paper discusses a theoretical and empirical approach to language fixedness that we have developed at the Institut für Deutsche Sprache (IDS) (‘Institute for German Language’) in Mannheim in the project Usuelle Worterbindungen(UWV) over the last decade. The analysis described is based on the Deutsches Referenzkorpus (‘German Reference Corpus’; DeReKo) which is located at the IDS. The corpus analysis tool used for accessing the corpus data is COSMAS II (CII) and – for statistical analysis – the IDS collocation analysis tool (Belica, 1995; CA). For detecting lexical patterns and describing their semantic and pragmatic nature we use the tool lexpan (or ‘Lexical Pattern Analyzer’) that was developed in our project. We discuss a new corpus-driven pattern dictionary that is relevant not only to the field of phraseology, but also to usage-based linguistics and lexicography as a whole.
CMC Corpora in DeReKo
(2017)
We introduce three types of corpora of computer-mediated communication that have recently been compiled at the Institute for the German Language or curated from an external project and included in DeReKo, the German Reference Corpus, namely Wikipedia (discussion) corpora, the Usenet news corpus, and the Dortmund Chat Corpus. The data and corpora have been converted to I5, the TEI customization to represent texts in DeReKo, and are researchable via the web-based IDS corpus research interfaces and in the case of Wikipedia and chat also downloadable from the IDS repository and download server, respectively.
This paper describes the efforts in the field of sustainability of the Institut für Deutsche Sprache (IDS) in Mannheim with respect to DEREKO (Deutsches Referenzkorpus) the Archive of General Reference Corpora of Contemporary Written German. With focus on re-usability and sustainability, we discuss its history and our future plans. We describe legal challenges related to the creation of a large and sustainable resource; sketch out the pipeline used to convert raw texts to the final corpus format and outline migration plans to TEI P5. Due to the fact, that the current version of the corpus management and query system is pushed towards its limits, we discuss the requirements for a new version which will be able to handle current and future DEREKO releases. Furthermore, we outline the institute’s plans in the field of digital preservation.
The paper discusses from various angles the morphosyntactic annotation of DeReKo, the Archive of General Reference Corpora of Contemporary Written German at the Institut für Deutsche Sprache (IDS), Mannheim. The paper is divided into two parts. The first part covers the practical and technical aspects of this endeavor. We present results from a recent evaluation of tools for the annotation of German text resources that have been applied to DeReKo. These tools include commercial products, especially Xerox' Finite State Tools and the Machinese products developed by the Finnish company Connexor Oy, as well as software for which academic licenses are available free of charge for academic institutions, e.g. Helmut Schmid's Tree Tagger. The second part focuses on the linguistic interpretability of the corpus annotations and more general methodological considerations concerning scientifically sound empirical linguistic research. The main challenge here is that unlike the texts themselves, the morphosyntactic annotations of DeReKo do not have the status of observed data; instead they constitute a theory and implementation-dependent interpretation. In addition, because of the enormous size of DeReKo, a systematic manual verification of the automatic annotations is not feasible. In consequence, the expected degree of inaccuracy is very high, particularly wherever linguistically challenging phenomena, such as lexical or grammatical variation, are concerned. Given these facts, a researcher using the annotations blindly will run the risk of not actually studying the language but rather the annotation tool or the theory behind it. The paper gives an overview of possible pitfalls and ways to circumvent them and discusses the opportunities offered by using annotations in corpus-based and corpus-driven grammatical research against the background of a scientifically sound methodology.
Usenet is a large online resource containing user-generated messages (news articles) organised in discussion groups (newsgroups) which deal with a wide variety of different topics. We describe the download, conversion, and annotation of a comprehensive German news corpus for integration in DeReKo, the German Reference Corpus hosted at the Institut für Deutsche Sprache in Mannheim.
Wikipedia is a valuable resource, useful as a lingustic corpus or a dataset for many kinds of research. We built corpora from Wikipedia articles and talk pages in the I5 format, a TEI customisation used in the German Reference Corpus (Deutsches Referenzkorpus - DeReKo). Our approach is a two-stage conversion combining parsing using the Sweble parser, and transformation using XSLT stylesheets. The conversion approach is able to successfully generate rich and valid corpora regardless of languages. We also introduce a method to segment user contributions in talk pages into postings.
We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging DeReKo, a very large general-purpose corpus of contemporary German (Kupietz et al., 2010). DeReKo 's strong dispersion wrt. genre, register and time forces us to base our decision for a specific NERC system on an evaluation performed on a representative sample of DeReKo instead of performance figures that have been reported for the individual NERC systems when evaluated on more uniform and less diverse data. We create and manually annotate such a representative sample as evaluation data for three different NERC systems, for each of which various models are learnt on multiple training data. The proposed sampling method can be viewed as a generally applicable method for sampling evaluation data from an unbalanced target corpus for any sort of natural language processing.
^This paper describes DeReKo (Deutsches Referenzkorpus), the Archive of General Reference Corpora of Contemporary Written German at the Institut für Deutsche Sprache (IDS) in Mannheim, and the rationale behind its development. We discuss its design, its legal background, how to access it, available metadata, linguistic annotation layers, underlying standards, ongoing developments, and aspects of using the archive for empirical linguistic research. The focus of the paper is on the advantages of DEREKO’s design as a primordial sample from which virtual corpora can be drawn for the specific purposes of individual studies. Both concepts, primordial sample and virtual corpus are explained and illustrated in detail. Furthermore, we describe in more detail how DEREKO deals with the fact that all its texts are subject to third parties’ intellectual property rights, and how it deals with the issue of replicability, which is particularly challenging given DEREKO’s dynamic growth and the possibility to construct from it an open number of virtual corpora.