Korpuslinguistik
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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.
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.
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.
^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.
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.
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 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.