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.
.. toctree::
:maxdepth: 2
:caption: User Documentation
user/getting_started
user/parser
user/data_model_utils
user/candidates
user/features
user/supervision
user/learning
user/packaging
user/config
user/faqs
.. toctree::
:maxdepth: 2
:caption: Developer Documentation
dev/changelog
dev/install
dev/tests
dev/codestyle
We gratefully acknowledge the support of DARPA under No. N66001-15-C-4043 (SIMPLEX), No. FA8750-17-2-0095 (D3M), No. FA8750-12-2-0335, and No. FA8750-13-2-0039; DOE under 108845; NIH under U54EB020405; ONR under No. N000141712266 and No. N000141310129; the Intel/NSF CPS Security grant No. 1505728; the Secure Internet of Things Project; Qualcomm; Ericsson; Analog Devices; the National Science Foundation Graduate Research Fellowship under Grant No. DGE-114747; the Stanford Finch Family Fellowship; the Moore Foundation; the Okawa Research Grant; American Family Insurance; Accenture; Toshiba; and members of the Stanford DAWN project: Intel, Microsoft, Google, Teradata, and VMware. We thank Holly Chiang, Bryan He, and Yuhao Zhang for helpful discussions. We also thank Prabal Dutta, Mark Horowitz, and Björn Hartmann for their feedback on early versions of this work. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views, policies, or endorsements, either expressed or implied, of DARPA, DOE, NIH, ONR, or the U.S. Government.