Natural Language Generation for the Semantic Web
There is a growing need in the Semantic Web (SW) community for technologies that give humans easy access to the machine-oriented Web of data. Because it maps data to text, Natural Language Generation (NLG) provides a natural mean for presenting this data in an organized, coherent and accessible way. Conversely, the representation languages used by the semantic web (e.g., OWL ontologies and RDF data) are a natural starting ground for NLG systems.
The aim of the Web-NLG project is to exploit this synergy between NLG and the Semantic Web and to further the development of robust and portable, high quality NLG systems capable of producing natural sounding text from SW data.
The project will build on an ongoing collaboration between LORIA (Nancy, France), the KRDB group at (Bolzano, Italy) and Stanford Research International (USA), bringing together high level academic partners with internationally recognised expertise in NLG (LORIA), Artificial Intelligence (SRI) and Knowledge Representation (KRDB).
The WebNLG project is a 3 year research project funded by the French National Research Agency (ANR)