The Common European Language Data Space (LDS) is an integral part of the EU data strategy, which aims at developing a single market for data. Its decentralised technical infrastructure and governance scheme are currently being developed by the LDS project, which also has dedicated tasks for proof-of-concept prototypes, handling legal aspects, raising awareness and promoting the LDS through events and social media channels. The LDS is part of a broader vision for establishing all necessary components to develop European large language models.

The European Language Grid (ELG) is a cloud platform for the whole European Language Technology community. While the EU project that developed the platform successfully concluded in June 2022, the ELG initiative has continued. This article provides a description of the current state of ELG in terms of user adoption and number of language resources and technologies available in early 2024. It also provides an overview of the various activities with regard to ELG since the end of the project and since the publication of the ELG book, especially the co-authors’ attempt to integrate the ELG platform into various data space initiatives. The article also provides an overview of the Digital Language Equality (DLE) dashboard and the current state of DLE in Europe.

Understanding the relation between the meanings of words is an important part of comprehending natural language. Prior work has either focused on analysing lexical semantic relations in word embeddings or probing pretrained language models (PLMs), with some exceptions. Given the rarity of highly multilingual benchmarks, it is unclear to what extent PLMs capture relational knowledge and are able to transfer it across languages. To start addressing this question, we propose MultiLexBATS, a multilingual parallel dataset of lexical semantic relations adapted from BATS in 15 languages including low-resource languages, such as Bambara, Lithuanian, and Albanian. As experiment on cross-lingual transfer of relational knowledge, we test the PLMs’ ability to (1) capture analogies across languages, and (2) predict translation targets. We find considerable differences across relation types and languages with a clear preference for hypernymy and antonymy as well as romance languages.

This paper describes the current status of the emerging OntoLex module for linguistic morphology. It serves as an update to the previous version of the vocabulary (Klimek et al. 2019). Whereas this earlier model was exclusively focusing on descriptive morphology and focused on applications in lexicography, we now present a novel part and a novel application of the vocabulary to applications in language technology, i.e., the rule-based generation of lexicons, introducing a dynamic component into OntoLex.

In recent times, more attention has been brought by the Human Language Technology (HLT) community to the legal framework for making available and reusing Language Resources (LR) and tools. Licensing is now an issue that is foreseen in most research projects and that is essential to provide legal certainty for repositories when distributing resources. Some repositories such as Zenodo or Quantum Stat do not offer the possibility to search for resources by licenses which can turn the searching for relevant resources a very complex task. Other repositories such as Hugging Face propose a search feature by license which may make it difficult to figure out what use can be made of such resources. During the European Language Grid (ELG) project, we moved a step forward to link metadata with the terms and conditions of use. In this paper, we document the process we undertook to categorize legal features of licenses listed in the SPDX license list and widely used in the HLT community as well as those licenses used within the ELG platform

The European Language Equality (ELE) project develops a strategic research, innovation and implementation agenda (SRIA) and a roadmap for achieving full digital language equality in Europe by 2030. Key component of the SRIA development is an accurate estimation of the current standing of languages with respect to their technological readiness. In this paper we present the empirical basis on which such estimation is grounded, its starting point and in particular the automatic and collaborative methods used for extending it. We focus on the collaborative expert activities, the challenges posed, and the solutions adopted. We also briefly present the dashboard application developed for querying and visualising the empirical data as well as monitoring and comparing the evolution of technological support within and across languages.

Europe is a multilingual society, in which dozens of languages are spoken. The only option to enable and to benefit from multilingualism is through Language Technologies (LT), i.e., Natural Language Processing and Speech Technologies. We describe the European Language Grid (ELG), which is targeted to evolve into the primary platform and marketplace for LT in Europe by providing one umbrella platform for the European LT landscape, including research and industry, enabling all stakeholders to upload, share and distribute their services, products and resources. At the end of our EU project, which will establish a legal entity in 2022, the ELG will provide access to approx. 1300 services for all European languages as well as thousands of data sets.

With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). European LT business is dominated by hundreds of SMEs and a few large players. Many are world-class, with technologies that outperform the global players. However, European LT business is also fragmented – by nation states, languages, verticals and sectors, significantly holding back its impact. The European Language Grid (ELG) project addresses this fragmentation by establishing the ELG as the primary platform for LT in Europe. The ELG is a scalable cloud platform, providing, in an easy-to-integrate way, access to hundreds of commercial and non-commercial LTs for all European languages, including running tools and services as well as data sets and resources. Once fully operational, it will enable the commercial and non-commercial European LT community to deposit and upload their technologies and data sets into the ELG, to deploy them through the grid, and to connect with other resources. The ELG will boost the Multilingual Digital Single Market towards a thriving European LT community, creating new jobs and opportunities. Furthermore, the ELG project organises two open calls for up to 20 pilot projects. It also sets up 32 national competence centres and the European LT Council for outreach and coordination purposes.

The current scientific and technological landscape is characterised by the increasing availability of data resources and processing tools and services. In this setting, metadata have emerged as a key factor facilitating management, sharing and usage of such digital assets. In this paper we present ELG-SHARE, a rich metadata schema catering for the description of Language Resources and Technologies (processing and generation services and tools, models, corpora, term lists, etc.), as well as related entities (e.g., organizations, projects, supporting documents, etc.). The schema powers the European Language Grid platform that aims to be the primary hub and marketplace for industry-relevant Language Technology in Europe. ELG-SHARE has been based on various metadata schemas, vocabularies, and ontologies, as well as related recommendations and guidelines.

With regard to the wider area of AI/LT platform interoperability, we concentrate on two core aspects: (1) cross-platform search and discovery of resources and services; (2) composition of cross-platform service workflows. We devise five different levels (of increasing complexity) of platform interoperability that we suggest to implement in a wider federation of AI/LT platforms. We illustrate the approach using the five emerging AI/LT platforms AI4EU, ELG, Lynx, QURATOR and SPEAKER.

In this paper, we study relations holding between language resources as implemented in activities concerned with their documentation. We envision the term “language resources” with an inclusive definition covering datasets (corpora, lexica, ontologies, grammars, etc.), tools (including web services, workflows, platforms etc.), related publications and documentation, specifications and guidelines. However, the scope of the paper is limited to relations holding for datasets and tools. The study fosuses on the META-SHARE infrastructure and the Linguistic Data Consortium and takes into account the ISOcat DCR relations. Based on this study, we propose a taxonomy of relations, discuss their semantics and provide specifications for their use in order to cater for semantic interoperability. Issues of granularity, redundancy in codification, naming conventions and semantics of the relations are presented.

This paper presents a metadata model for the description of language resources proposed in the framework of the META-SHARE infrastructure, aiming to cover both datasets and tools/technologies used for their processing. It places the model in the overall framework of metadata models, describes the basic principles and features of the model, elaborates on the distinction between minimal and maximal versions thereof, briefly presents the integrated environment supporting the LRs description and search and retrieval processes and concludes with work to be done in the future for the improvement of the model.

This paper reports on the multilingual Language Resources (MLRs), i.e. parallel corpora and terminological lexicons for less widely digitally available languages, that have been developed in the INTERA project and the methodology adopted for their production. Special emphasis is given to the reality factors that have influenced the MLRs development approach and their final constitution. Building on the experience gained in the project, a production model has been elaborated, suggesting ways and techniques that can be exploited in order to improve LRs production taking into account realistic issues.