KBpedia is a robust knowledge structure for knowledge representation, management and use. Possible uses include:

  • A coherent and computable overlay to both Wikipedia and Wikidata
  • Integrating domain data
  • Fine-grained entity identification, extraction and tagging
  • Faceted, semantic search and retrieval
  • Mapping and integration of external datasets
  • Natural language processing and computational linguistics
  • Knowledge graph creation, extension and maintenance
  • Tailored filtering, slicing-and-dicing, and extraction of domain knowledge structures
  • Data harvesting, transformation and ingest
  • A fast and clean source for word embedding models
  • A coherent framework for graph embedding models
  • Data interoperability, re-use of existing content and data assets, and knowledge discovery
  • Supervised, semi-supervised and distant supervised machine learning for:
    • Typing, classification, extraction, and tagging of entities, attributes and relations
  • Unsupervised and deep learning.

See further the specific use cases.