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 ACM SIGMOD Dissertation Award, as well as, 10 years later, the Test-of-Time Award of The Web Conference 2018. Fabian was a postdoctoral fellow at Microsoft Research and at INRIA Saclay. Then he led an independent 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.
https://suchanek.name

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Public Audience

English

60 Minutes

Saarbrücken

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.

Gerhard Weikum

+49 681 9325 5000

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