End Date: 31/05/2029
Funding: Horizon Europe Framework Programme (HORIZON)
Project Leader: Vacalopoulou Anna
The project proposes valuable enhancement of current AI foundation models and an upgrade of the European Lexicographic Infrastructure (ELEXIS), which resulted from a Horizon 2020 project with the same title (2018-2022). The upgrade represents a transformative reconstruction of the infrastructure, based on recent developments in AI, in particular related to the emergence of LLMs. Besides the integration of nation-al, regional, and institutional efforts in the field of lexicography, the new infrastructure will offer upgraded technology, language data, tools, and services that are crucial for improving transformer-based models with multilingual knowledge management originating from high-quality lexicographic resources. The advent of machine-readable knowledge representations (knowledge bases and graphs) that are linguistically sound and can be injected into LLMs, enables the introduction of a virtuous cycle where the relevance of the integrated linguistic knowledge is verified by better outputs from LLM applications that, subsequently, can be used for improving knowledge representations and language data. To verify the effect of incorporating linguistic knowledge in LLMs, the creation of reliable benchmarks and other means of evaluation of machine generated output is foreseen as a result. As such, the infra-structure design will contribute to the yet unresolved tasks of Natural Language Understanding. The establishment of a new virtual lexicographic infrastructure will be carried out by a broad and diverse consortium, including partners from all relevant fields: lexicography, Computational Linguistics, and AI. For long-term sustainability, the infrastructure will rely on two prominent infrastructural initiatives: CLARIN ERIC, as one of the ESFRI infrastructures, and ALT-EDIC, as the new pan-European initiative dedicated to the development of European open massively multilingual language models.
ILSP’s contribution to the project draws on its experience in the critical areas of lexicography, computational linguistics and artificial intelligence.