/ Natural Language Processing

A knowledge base construction engine for richly formatted data

A knowledge base construction engine for richly formatted data

Fonduer

Fonduer is a framework for building knowledge base construction (KBC) applications from richy formatted data and is implemented as a library on top of a modified version of Snorkel.

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. If you have questions, please use our Mailing List.

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:

@inproceedings{wu2017fonduer,
  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}
}

GitHub