The NoRDF project “Modeling and Extracting Complex Information from Natural Language Text” is a scientific project at Télécom Paris that aims at modeling and extracting complex information from natural language texts.

More precisely, its objective is to enrich knowledge bases with events, causalities, precedences, stories, negations and beliefs. It aims to extract this type of information at scale from structured and unstructured sources and to allow the machine to reason about this information, i.e. to apply logical arguments to arrive at an argued conclusion. To this end, its initiators wish to bring together research on knowledge representation, reasoning and information extraction.

The NoRDF Project is a chair selected and financially supported by the French National Research Agency (ANR) and the Defense Innovation Agency (AID) as part of the National Program for AI. The project has a total budget of 1.3 million euros for a period of four years. It also relies on the experience, use cases and financial support of four industrial partners: Converteo, EDF, Groupe BPCE and Schlumberger.

It is led on the academic level by its holder, Professor Fabian Suchanek, and his co-leader, Professor Chloé Clavel, professors at Télécom Paris, Institut Polytechnique de Paris.