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It is well known that the distribution of lexical and grammatical patterns is size- and register-sensitive (Biber 1986, and later publications). This fact alone presents a challenge to many corpus-oriented linguistic studies focusing on a single language. When it comes to cross-linguistic studies using corpora, the challenge becomes even greater due to the lack of high-quality multilingual corpora (Kupietz et al. 2020; Kupietz/Trawiński 2022), which are comparable with respect to the size and the register. That was the motivation for the creation of the European Reference Corpus EuReCo, an initiative started in 2013 at the Leibniz Institute for the German Language (IDS) together with several European partners (Kupietz et al. 2020). EuReCo is an emerging federated corpus, with large virtual comparable corpora across various languages and with an infrastructure supporting contrastive research. The core of the infrastructure is KorAP (Diewald et al. 2016), a scalable open-source platform supporting the analysis and visualisation of properties of texts annotated by multiple and potentially conflicting information layers, and supporting several corpus query languages. Until recently, EuReCo consisted of three monolingual subparts: the German Reference Corpus DeReKo (Kupietz et al. 2018), the Reference Corpus of Contemporary Romanian Language (Barbu Mititelu/Tufiş/Irimia 2018), and the Hungarian National Corpus (Váradi 2002). The goal of the present submission is twofold. On the one hand, it reports about the new component of EuReCo: a sample of the National Corpus of Polish (Przepiórkowski et al. 2010). On the other hand, it presents the results of a new pilot study using the newly extended EuReCo. This pilot study investigates selected Polish collocations involving light verbs and their prepositional / nominal complements (Fig. 1) and extends the collocation analyses of German, Romanian and Hungarian (Fig. 2) discussed in Kupietz/Trawiński (2022).
The International Comparable Corpus (ICC) (Kirk/Čermáková 2017; Čermáková et al. 2021) is an open initiative which aims to improve the empirical basis for contrastive linguistics by compiling comparable corpora for many languages and making them as freely available as possible as well as providing tools with which they can easily be queried and analysed. In this contribution we present the first release of written language parts of the ICC which includes corpora for Chinese, Czech, English, German, Irish (partly), and Norwegian. Each of the released corpora contains 400k words distributed over 14 different text categories according to the ICC specifications. Our poster covers the design basics of the ICC, its TEI encoding, a demonstration of using the ICC via different query tools, and an outlook on future plans.
Similar to the European Reference Corpus EuReCo (Kupietz et al. 2020), ICC follows the approach of reusing existing linguistic resources wherever possible in order to cover as many languages as possible with realistic effort in as short a time as possible. In contrast to EuReCo, however, comparable corpus pairs are not defined dynamically in the usage phase, but the compositions of the corpora are fixed in the ICC design. The approaches are thus complementary in this respect. The design principles and composition of the ICC are based on those of the International Corpus of English (ICE) (Greenbaum (ed.) 1996), with the deviation that the ICC includes the additional text category blog post and excludes spoken legal texts (see Čermáková et al. 2021 for details). ICC’s fixed-design approach has the advantage that all single-language corpora in the ICC have the same composition with respect to the selected text types and that this guarantees that the selected broad spectrum of potential influencing variables for linguistic variation is always represented. The disadvantage, however, is that this can only be achieved for quite small corpora and that the generalisability of comparative findings based on the ICC corpora will often need to be checked on larger monolingual corpora or translation corpora (Čermáková/Ebeling/Oksefjell Ebeling forthcoming). Arguing that such issues with comparability and representativeness are inevitable, in one way or the other, and need to be dealt with, our poster will discuss and exemplify the text selections in more detail.
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.
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 paper reports on recent developments within the European Reference Corpus EuReCo, an open initiative that aims at providing and using virtual and dynamically definable comparable corpora based on existing national, reference or other large corpora. Given the well-known shortcomings of other types of multilingual corpora such as parallel/translation corpora (shining-through effects, over-normalization, simplification, etc.) or web-based comparable corpora (covering only web material), EuReCo provides a unique linguistic resource offering new perspectives for fine-grained contrastive research on authentic cross-linguistic data, applications in translation studies and foreign language teaching and learning.
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.
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.
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-ofthe-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.
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.
Twitter data is used in a wide variety of research disciplines in Social Sciences and Humanities. Although most Twitter data is publicly available, its re-use and sharing raise many legal questions related to intellectual property and personal data protection. Moreover, the use of Twitter and its content is subject to the Terms of Service, which also regulate re-use and sharing. This extended abstract provides a brief analysis of these issues and introduces the new Academic Research product track, which enables authorized researchers to access Twitter API on a preferential basis.
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.
This paper reports on the efforts of twelve national teams in building the International Comparable Corpus (ICC; https://korpus.cz/icc) that will contain highly comparable datasets of spoken, written and electronic registers. The languages currently covered are Czech, Finnish, French, German, Irish, Italian, Norwegian, Polish, Slovak, Swedish and, more recently, Chinese, as well as English, which is considered to be the pivot language. The goal of the project is to provide much-needed data for contrastive corpus-based linguistics. The ICC corpus is committed to the idea of re-using existing multilingual resources as much as possible and the design is modelled, with various adjustments, on the International Corpus of English (ICE). As such, ICC will contain approximately the same balance of forty percent of written language and 60 percent of spoken language distributed across 27 different text types and contexts. A number of issues encountered by the project teams are discussed, ranging from copyright and data sustainability to technical advances in data distribution.
In this paper, we present our experiences and decisions in dealing with challenges in developing, maintaining and operating online research software tools in the field of linguistics. In particular, we highlight reproducibility, dependability, and security as important aspects of quality management – taking into account the special circumstances in which research software
is usually created.
We evaluate a graph-based dependency parser on DeReKo, a large corpus of contemporary German. The dependency parser is trained on the German dataset from the SPMRL 2014 Shared Task which contains text from the news domain, whereas DeReKo also covers other domains including fiction, science, and technology. To avoid the need for costly manual annotation of the corpus, we use the parser’s probability estimates for unlabeled and labeled attachment as main evaluation criterion. We show that these probability estimates are highly correlated with the actual attachment scores on a manually annotated test set. On this basis, we compare estimated parsing scores for the individual domains in DeReKo, and show that the scores decrease with increasing distance of a domain to the training corpus.
This paper addresses long-term archival for large corpora. Three aspects specific to language resources are focused, namely (1) the removal of resources for legal reasons, (2) versioning of (unchanged) objects in constantly growing resources, especially where objects can be part of multiple releases but also part of different collections, and (3) the conversion of data to new formats for digital preservation. It is motivated why language resources may have to be changed, and why formats may need to be converted. As a solution, the use of an intermediate proxy object called a signpost is suggested. The approach will be exemplified with respect to the corpora of the Leibniz Institute for the German Language in Mannheim, namely the German Reference Corpus (DeReKo) and the Archive for Spoken German (AGD).
This paper reports on the latest developments of the European Reference Corpus EuReCo and the German Reference Corpus in relation to three of the most important CMLC topics: interoperability, collaboration on corpus infrastructure building, and legal issues. Concerning interoperability, we present new ways to access DeReKo via KorAP on the API and on the plugin level. In addition we report about advancements in the EuReCo- and ICC-initiatives with the provision of comparable corpora, and about recent problems with license acquisitions and our solution approaches using an indemnification clause and model licenses that include scientific exploitation.
Einleitung
(2018)
Das hier vorgeführte Schienenbild ist das in Anlehnung an Wittenburg (2009) als Erweiterungsinstrument gewählte Mittel in dem Versuch, Computertechnologie, linguistische Forschung und Vernetzung am Institut für Deutsche Sprache in deren rasch wachsenden Vielschichtigkeit zu beschreiben. Hier werden u. a. drei Blickwinkel, der des Technologie entwickelnden Wissenschaftlers, des entwickelnden Nutzers und des Nutzers von Informationstechnologie in der linguistischen Forschung vereint und um eine für den Sprachvergleich neue Dimension, die sprachspezifische Parameter von Analyseinstrumenten miteinander harmonisiert, erweitert.
This paper discusses current trends in DeReKo, the German Reference Corpus, concerning legal issues around the recent German copyright reform with positive implications for corpus building and corpus linguistics in general, recent corpus extensions in the genres of popular magazines, journals, historical texts, and web-based football reports. Besides, DeReKo is finally accessible via the new
corpus research platform KorAP, offering registered users several news features in comparison with its predecessor COSMAS II.
Sehr große Korpora – wie das Deutsche Referenzkorpus DeReKo – bieten eine breite Basis für die empirische Forschung. Sie bringen aber auch Herausforderungen mit sich, da sich weder Eigenschaften ihrer Zusammensetzung noch derer von Recherche- und Analyseergebnissen mit einfachen Mitteln erschließen lassen. Dafür bedarf es Verfahren geschickter Sortierung, Gruppierung oder des Clusterings, kurzum: strukturentdeckender Methoden. In Kombination mit Visualisierungstechniken kann so die Wahrnehmung bestimmter Eigenschaften und Zusammenhänge unterstützt und die Aufmerksamkeit auf bestimmte Phänomene, ggf. in Anlehnung an präferenzrelationale Befunde, gelenkt werden. Neben der illustrativen Funktion geht es in diesem Beitrag vor allem um das erkenntnisleitende Potenzial derartiger Verfahren in Kombination. Aus verschiedenen Bereichen werden Beispiele gezeigt, die am IDS oder in Kooperationen zum Einsatz kommen, sowohl zur dokumentarischen und reflexiven Kontrolle von Eigenschaften der Korpuszusammensetzung als auch hinsichtlich korpusanalytischer Methodik, um die qualitative Interpretation von Analysebefunden und die Abduktion von Hypothesen stimulierend zu unterstützen.
Einleitung
(2018)
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.
Valenz und Kookkurrenz
(2015)
Der Beitrag beschäftigt sich mit der Frage, wie und inwieweit korpusbasierte Ansätze zur Untersuchung und Bewertung von Sprachwandel beitragen können. Die Bewertung von Sprachwandel erscheint in dieser Hinsicht interessant, da sie erstens von größerem öffentlichen Interesse ist, zweitens nicht zu den Kernthemen der Sprachwissenschaft zählt und drittens sowohl die geisteswissenschaftlichen Aspekte der Sprachwissenschaft berührt als auch die empirischen, die eher für die so genannten harten Wissenschaften typisch sind. Letzteres trifft bei der Frage nach Sprachverfall (gutem vs. schlechtem Deutsch diachron) vermutlich unbestrittener zu als bei der Frage nach richtigem vs. falschem Deutsch, da zu ihrer Beantwortung offensichtlich einerseits empirische, messbare Kriterien herangezogen werden müssen, andererseits aber auch weitere Kriterien notwendig sind und es außerdem einer Entscheidung zur Einordnung und Gewichtung der verschiedenartigen Kriterien sowie einer Begründung dieser Entscheidung bedarf. Zur Annäherung an die Fragestellung werden zunächst gängige, leicht operationalisierbare Hypothesen zu Symptomen eines potenziellen Verfalls des Deutschen auf verschiedenen DeReKo-basierten Korpora überprüft und im Hinblick auf ihre Verallgemeinerbarkeit und Tragweite diskutiert. Im zweiten Teil werden weitere empirische Ansätze zur Untersuchung von Wandel, Variation und Dynamik skizziert, die zur Diskussion spezieller Aspekte von Sprachverfall beitragen könnten. Im Schlussteil werden die vorgestellten Ansätze in den Gesamtkontext einer sprachwissenschaftlichen Untersuchung von Sprachverfall gestellt und vor dem Hintergrund seines gesellschaftlichen Diskurses reflektiert.