Korpuslinguistik
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The article focuses on determining responsible parties and the division of potential liability arising from sharing language data (LD) containing personal data (PD). A key issue here is to identify who has to make sure and guarantee the GDPR compliance. The authors aim to answer 1) whether an individual researcher is a controller and 2) whether sharing LD results in joint controllership or separate controllership (whether the data's transferee becomes the controller, the joint controller or the processor). The article also analyses the legal relations of parties involved in data sharing and potential liability. The final section outlines data sharing in the CLARIN context. The analysis serves as a preliminary analytical background for redesigning the CLARIN contractual framework for sharing data.
N-grams are of utmost importance for modern linguistics and language technology. The legal status of n-grams, however, raises many practical questions. Traditionally, text snippets are considered copyrightable if they meet the originality criterion, but no clear indicators as to the minimum length of original snippets exist; moreover, the solutions adopted in some EU Member States (the paper cites German and French law as examples) are considerably different. Furthermore, recent developments in EU law (the CJEU's Pelham decision and the new right of press publishers) also provide interesting arguments in this debate. The paper presents the existing approaches to the legal protection of n-grams and tries to formulate some clear guidelines as to the length of n-grams that can be freely used and shared.
This paper describes the TEI-based ISO standard 2462:2016 “Transcription of spoken language” and other formats used within CLARIN for spoken language resources. It assesses the current state of support for the standard and the interoperability between these formats and with relevant tools and services. The main idea behind the paper is that a digital infrastructure providing language resources and services to researchers should also allow the combined use of resources and/or services from different contexts. This requires syntactic and semantic interoperability. We propose a solution based on the ISO/TEI format and describe the necessary steps for this format to work as an exchange format with basic semantic interoperability for spoken language resources across the CLARIN infrastructure and beyond.
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.
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.