  A person ontology comprising concepts, attributes and relationships of people
has a number of applications in data protection, didentification, population of
knowledge graphs for business intelligence and fraud prevention. While
artificial neural networks have led to improvements in Entity Recognition,
Entity Classification, and Relation Extraction, creating an ontology largely
remains a manual process, because it requires a fixed set of semantic relations
between concepts. In this work, we present a system for automatically
populating a person ontology graph from unstructured data using neural models
for Entity Classification and Relation Extraction. We introduce a new dataset
for these tasks and discuss our results.
