Towards the LinkEn Knowledge Base. A Neuro-Symbolic Approach to Build a Linked Data Hub for English Lemmas with Large Language Models

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.

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