RDF data extracted automatically often contain long textual literals. This paper shows how to use natural language processing techniques to automatically generate specific RDF triples from the information in the literals. We look specifically at drug indications found in the DailyMed dataset. We develop knowledge schemas to capture its information as well as precise syntactic-based methods of knowledge extraction to automatically generate instances of these schemas from textual data.
['Michel Gagnon', 'Caroline Barrière', 'Eric Charton']
Full syntactic parsing for enrichment of RDF dataset