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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).
Standards in CLARIN
(2022)
This chapter looks at a fragment of the ongoing work of the CLARIN Standards Committee (CSC) on producing a shared set of recommendations on standards, formats, and related best practices supported by the CLARIN infrastructure and its participating centres. What might at first glance seem to be a straightforward goal has over the years proven to be rather complex, reflecting the robustness and heterogeneity of the emerging distributed digital research infrastructure and the various disciplines and research traditions of the language-based humanities that it serves and represents, and therefore part of the chapter reviews the various initiatives and proposals that strove to produce helpful standards-related guidance. The focus turns next to a subtask initiated in late 2019, its scope narrowed to one of the core activities and responsibilities of CLARIN backbone centres, namely the provision of data deposition services. Centres are obligated to publish their recom-mendations concerning the repertoire of data formats that are best suited for their research profiles. We look at how this requirement has been met by the particular centres and suggest that having centres maintain their information in the Standards Information System (SIS) is the way to improve on the current state of affairs.
Contents:
1. Vasile Pais, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, Roxana Micu and Carol Luca Gasan: Challenges in Creating a Representative Corpus of Romanian Micro-Blogging Text. Pp. 1-7
2. Modest von Korff: Exhaustive Indexing of PubMed Records with Medical Subject Headings. Pp. 8-15
3. Luca Brigada Villa: UDeasy: a Tool for Querying Treebanks in CoNLL-U Format. Pp. 16-19
4. Nils Diewald: Matrix and Double-Array Representations for Efficient Finite State Tokenization. Pp. 20-26
5. Peter Fankhauser and Marc Kupietz: Count-Based and Predictive Language Models for Exploring DeReKo. Pp. 27-31
6. Hanno Biber: “The word expired when that world awoke.” New Challenges for Research with Large Text Corpora and Corpus-Based Discourse Studies in Totalitarian Times. Pp. 32-35
This paper presents an algorithm and an implementation for efficient tokenization of texts of space-delimited languages based on a deterministic finite state automaton. Two representations of the underlying data structure are presented and a model implementation for German is compared with state-of-the-art approaches. The presented solution is faster than other tools while maintaining comparable quality.
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.
Dieser Beitrag präsentiert die neue multilinguale Ressource CoMParS (Collection of Multilingual Parallel Sequences). CoMParS versteht sich als eine funktional-semantisch orientierte Datenbank von Parallelsequenzen des Deutschen und anderer europäischer Sprachen, in der alle Daten neben den sprachspezifischen und universellen (im Sinne von Universal Dependencies) morphosyntaktischen Annotationen auch nach sprachübergreifenden funktional-semantischen Informationen auf der neudefinierten Annotationsebene Functional Domains annotiert und auf mehreren Ebenen (auch ebenenübergreifend) miteinander verlinkt sind. CoMParS wird in TEI P5 XML kodiert und sowohl als monolinguale wie auch als multilinguale Sprachressource modelliert.
Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus
(2021)
Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics. However, most of these large raw corpora are either available only for English or not available to the general public due to copyright issues. Nevertheless, there are some examples of freely available multilingual corpora for training Deep Learning NLP models, such as the OSCAR and Paracrawl corpora. However, they have quality issues, especially for low-resource languages. Moreover, recreating or updating these corpora is very complex. In this work, we try to reproduce and improve the goclassy pipeline used to create the OSCAR corpus. We propose a new pipeline that is faster, modular, parameterizable, and well documented. We use it to create a corpus similar to OSCAR but larger and based on recent data. Also, unlike OSCAR, the metadata information is at the document level. We release our pipeline under an open source license and publish the corpus under a research-only license.
Making research data publicly available for evaluation or reuse is a fundamental part of good scientific practice. However, regulations such as copyright law can prevent this practice and thereby hamper scientific progress. In Germany, text-based research disciplines have for a long time been mostly unable to publish corpora made from material outside of the public domain, effectively excluding contemporary works. While there are approaches to obfuscate text material in a way that it is no longer covered by the original copyright, many use cases still require the raw textual context for evaluation or follow-up research. Recent changes in copyright now permit text and data mining on copyrighted works. However, questions regarding reusability and sharing of such corpora at a later time are still not answered to a satisfying degree. We propose a workflow that allows interested third parties to access customized excerpts of protected corpora in accordance with current German copyright law and the soon to be implemented guidelines of the Digital Single Market directive. Our prototype is a very lightweight web interface that builds on commonly used repository software and web standards.
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.
Contents:
1. Julien Abadji, Pedro Javier Ortiz Suárez, Laurent Romary and Benoît Sagot: "Ungoliant: An Optimized Pipeline for the Generation of a Very Large-Scale Multilingual Web Corpus", S.1-9.
2. Markus Gärtner, Felicitas Kleinkopf, Melanie Andresen and Sibylle Hermann: "Corpus Reusability and Copyright - Challenges and Opportunities", S.10-19.
3. Nils Diewald, Eliza Margaretha and Marc Kupietz: "Lessons learned in Quality Management for Online Research Software Tools in Linguistics", S.20-26.