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Starting January 2026, we are going to start a Lunch Lecture Series associated to Working Group on "Knowledge Graph-aware Services and Methods" of GOBLIN Cost Action. This page lists these talks which will also be featured on the official website of GOBLIN.
Starting January 2026, we are going to start a Lunch Lecture Series associated to Working Group on "Knowledge Graph-aware Services and Methods" of GOBLIN Cost Action. This page lists these talks which will also be featured on the official website of GOBLIN.
Title: Data Taste: Foregrounding Choices in Knowledge Graph Construction
Title: Data Taste: Foregrounding Choices in Knowledge Graph Construction
Speaker: Paul Groth
When: January 23, 2026 at 13:00 (Paris time)
Where: Zoom (Registration Link: https://forms.gle/tLYJ2GeF9L6nvt7b7 - Register by January 20, 2026)
Abstract. Large Language Models (LLMs) have provided a powerful new capabilities for knowledge graph construction. In particular, they have dramatically decreased the cost of knowledge acquisition (e.g. information extraction and knowledge probing from LLMs). This has brought a renewed focus on other knowledge engineering tasks that are part of the knowledge graph construction process - such as modelling and consensus formation. In this talk, I argue that given the increasing performance of LLMs our attention should turn towards the choices made in the construction process and that value accrues to making good choices - or having good taste. I give concrete examples how to realise this in different stages of KG construction both by humans and with LLMs.
Biography. Paul Groth is Professor of Algorithmic Data Science at the University of Amsterdam where he leads the Intelligent Data Engineering Lab (INDElab) and is scientific director of the UvA’s Data Science Center. He holds a Ph.D. in Computer Science from the University of Southampton (2007) and has done research at the University of Southern California, the Vrije Universiteit Amsterdam and Elsevier Labs. His research focuses on intelligent systems for dealing with large amounts of diverse contextualized data with a particular focus on web and science applications. This includes research in data provenance, data integration and knowledge sharing.
Previously, Paul led the design of a number of large scale data integration and knowledge graph construction efforts in the biomedical domain. Paul was co-chair of the W3C Provenance Working Group that created a standard for data provenance interchange. He has also contributed to the emergence of community initiatives to build a better scholarly data ecosystem including altmetrics and the FAIR data principles. Paul is co-author of “Provenance: an Introduction to PROV” and “The Semantic Web Primer: 3rd Edition” as well as numerous academic articles. You can find him on twitter: @pgroth .
Title: On Language Models and Knowledge Bases
Title: On Language Models and Knowledge Bases
Speaker: Fabian Suchanek
When: February 20, 2026 at 13:00 (Paris time)
Where: Zoom
Abstract. Language Models have brought major breakthroughs in natural language processing. Notwithstanding this success, I will show that certain applications still need symbolic representations. I will then show how different methods (language models and others) can be harnessed to build such symbolic representations in the form of knowledge bases. I will highlight several challenges in this endeavor, from finding good embeddings to improving entity linking and dealing with fallacies and textual entailment. I will also discuss how language models can be evaluated along several dimensions. Finally, I will talk about the knowledge bases themselves, most notably our YAGO project. I will present our work on detecting and alleviating incompleteness in knowledge bases, on querying the data, on using the data for the digital humanities, and on reasoning on beliefs.
Biography. Fabian M. Suchanek is a full professor at the Institut Polytechnique de Paris in France. He obtained his doctorate at the Max-Planck Institute for Computer Science in Germany. In his thesis, Fabian developed the YAGO knowledge base, one of the largest public knowledge bases, which earned him an honorable mention of the SIGMOD thesis prize, as well as, 10 years later, the “Test of Time” of The Web Conference 2018. Fabian was a postdoctoral fellow at Microsoft Research in Silicon Valley and at INRIA Saclay. Then he led a research group at the Max-Planck Institute for Computer Science. In 2013, he became an associate professor, and in 2016 a full professor at Télécom Paris, now part of Institut Polytechnique de Paris. With his students, Fabian works on natural language processing, neuro-symbolic reasoning, information extraction, rule mining, and knowledge graph management. He has published over 100 scientific papers, and his work has been cited over 19,000 times.
Title: TBD
Title: TBD
Speaker: Claudia d'Amato
When: March, 2026 at 13:00 (Paris time)
Where: Zoom
Abstract.
Biography.
Title: TBD
Title: TBD
Speaker: Heiko Paulheim
When: April 24, 2026 at 13:00 (Paris time)
Where: Zoom
Abstract.
Biography.
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