@prefix this: . @prefix sub: . @prefix schema: . @prefix np: . @prefix dct: . @prefix pav: . @prefix nt: . @prefix npx: . @prefix xsd: . @prefix rdfs: . @prefix prov: . @prefix wd: . @prefix foaf: . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { sub:meaningful-data-llms a wd:Q604733; dct:description "

Large Language Models have enabled significant improvements across a wide range of Natural Language Processing tasks, making them the interface of choice for many novel data exploration systems. However, LLMs also have known shortcomings, including hallucinations and cut-off dates. In this talk, I will present the important role of Knowledge Graphs in complementing LLMs with accurate and up-to-date information. The SIB Swiss Institute of Bioinformatics has a long-standing expertise in curating and maintaining high-quality, interoperable knowledge graphs across diverse bioinformatics disciplines. I will discuss how LLMs provide today an important opportunity to democratize access to these scientific data for a wider audience of researchers, if used appropriately. Finally, I will demonstrate a concrete application leveraging LLMs for Knowledge Graph Question Answering.

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