Modeling and extracting complex information from natural language text
As a result of the Covid-19 outbreak, we are unfortunately forced to cancel this webinar which was scheduled for Monday 28th September.
A new date will be proposed soon: do not hesitate to register via the form in the link below to be informed.
The NoRDF Project is a scientific project at Télécom Paris, Institut Polytechnique de Paris that aims to model and extract complex information from natural language text. More precisely, we want to enrich knowledge bases with events, causation, precedence, stories, negation, and beliefs. In particular, we will investigate the expression of sentiment. We want to extract this type of information at scale from structured and unstructured sources, and we want to allow machines to reason on it. The project brings together research on knowledge representation, on reasoning, and on 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.
In the first part of the talk, we will give a general overview of the project. In the second part of the talk, we will highlight the challenges for sentiment analysis in human-human and human-agent interactions.