HazyResearch / fonduer

A knowledge base construction engine for richly formatted data

Fonduer is a Python package and framework for building knowledge base construction (KBC) applications from richly formatted data.

Note that Fonduer is still actively under development, so feedback and contributions are welcome. Submit bugs in the Issues section or feel free to submit your contributions as a pull request.

Getting Started

Check out our Getting Started Guide to get up and running with Fonduer.

Learning how to use Fonduer

The Fonduer tutorials cover the Fonduer workflow, showing how to extract relations from hardware datasheets and scientific literature.

Reference

Fonduer: Knowledge Base Construction from Richly Formatted Data (blog):

@inproceedings{wu2018fonduer,
  title={Fonduer: Knowledge Base Construction from Richly Formatted Data},
  author={Wu, Sen and Hsiao, Luke and Cheng, Xiao and Hancock, Braden and Rekatsinas, Theodoros and Levis, Philip and R{\'e}, Christopher},
  booktitle={Proceedings of the 2018 International Conference on Management of Data},
  pages={1301--1316},
  year={2018},
  organization={ACM}
}

Acknowledgements

Fonduer leverages the work of Emmental and Snorkel.