Four positions opened to work on extracting complex information from natural language text

The NoRDF Projet, a French Research Agency (ANR) Research Chair issued from the French AI for Humanity national plan, aims to model and extract complex information from natural language text. More precisely, its goal is to enrich knowledge bases with events, causation, conditions, precedence, stories, negation, and beliefs. In particular, it will investigate the expression of sentiment.

The NoRDF Projet is lead by Professor Fabian Suchanek from Télécom Paris, Institut Polytechnique de Paris, a specialist of knowledge bases and ontologies and co-creator of the renowned YAGO knowledge base. The project brings together research on knowledge representation, reasoning, and information extraction, and aims to be useful for applications such as fake news detection, the modeling of controversies, or the analysis of the e-reputation of a company.

Funded by the French Research Agency, the project benefits of a total funding of 1.3m € and runs from 2020 to 2024. It also draws from the experience, the use cases, and the support of four industrial partners: EDF, Groupe BPCE, Schlumberger and Converteo.

There are presently four positions (Two PhD, one Postdoc, and one Engineer) open to work on the topics of the project, and more generally on anything related to knowledge bases, natural language processing, automated reasoning, knowledge representation, information extraction…