@inproceedings{augello-passarotti-2026-towards,
    title = "Towards the {L}ink{E}n Knowledge Base. A Neuro-Symbolic Approach to Build a Linked Data Hub for {E}nglish Lemmas with Large Language Models",
    author = "Augello, Lorenzo  and
      Passarotti, Marco",
    editor = "McCrae, John P.  and
      Gkirtzou, Katerina  and
      Khan, Fahad  and
      Martin Chozas, Patricia  and
      Carvalho, Sara  and
      Canning, Erin",
    booktitle = "Proceedings of 10th Workshop on Linked Data in Linguistics ({LDL}-2026)",
    month = may,
    year = "2026",
    address = "Palma, Mallorca (Spain)",
    publisher = "ELRA Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/ingest-nlpsi/2026.ldl-1.2/",
    doi = "10.63317/5ndvctbdvkb7",
    pages = "13--21",
    abstract = "This paper presents the first core component of LinkEn, a knowledge base of interoperable language resources for English adhering to Linked Open Data principles. With this initial step towards a broader infrastructure, we focus on the development of a lemma-centered hub designed to enable interoperability between distributed lexical resources, corpora, and linguistic annotations. The modeling is inspired by the LiLa Knowledge Base for Latin and the OntoLex-Lemon model, ensuring compatibility with existing lemma-centric knowledge graphs and enabling future cross-linguistic interoperability. Rather than relying solely on manual knowledge graph construction and significant human effort, the lemma bank has been developed through a hybrid neuro-symbolic pipeline that integrates large language models into the generation of RDF data under explicit ontological constraints. This approach combines automated generation with ontology-driven supervision and evaluation, enabling scalable yet controlled construction of structured lexical knowledge. By presenting the first steps towards the LinkEn Knowledge Base, this paper contributes both a new lemma bank for English and an experimental methodology for the semi-automatic creation of Linked Data based knowledge graphs."
}