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.
- Pub Date:
- January 2020
- Computer Science - Artificial Intelligence;
- Computer Science - Computation and Language;
- Computer Science - Information Retrieval
- 6 pages, 10 figures. arXiv admin note: substantial text overlap with arXiv:1811.09368