Welcome to IEPY's documentation!
IEPY is an open source tool for Information Extraction focused on Relation Extraction.
To give an example of Relation Extraction, if we are trying to find a birth date in:
"John von Neumann (December 28, 1903 – February 8, 1957) was a Hungarian and American pure and applied mathematician, physicist, inventor and polymath."
then IEPY's task is to identify "
John von Neumann" and
December 28, 1903" as the subject and object entities of the "
was born in"
- It's aimed at:
- :doc:`A corpus annotation tool <corpus_labeling>` with a web-based UI
- :doc:`An active learning relation extraction tool <active_learning_tutorial>` pre-configured with convenient defaults.
- :doc:`A rule based relation extraction tool <rules_tutorial>` for cases where the documents are semi-structured or high precision is required.
- A web-based user interface that:
- Allows layman users to control some aspects of IEPY.
- Allows decentralization of human input.
- A shallow entity ontology with coreference resolution via Stanford CoreNLP
- :doc:`An easily hack-able active learning core <how_to_hack>`, ideal for scientist wanting to experiment with new algorithms.
.. toctree:: :maxdepth: 2 installation tutorial instantiation active_learning_tutorial rules_tutorial preprocess gazettes corpus_labeling how_to_hack troubleshooting language
- Rafael Carrascosa <email@example.com> (rafacarrascosa at github)
- Javier Mansilla <firstname.lastname@example.org> (jmansilla at github)
- Gonzalo García Berrotarán <email@example.com> (j0hn at github)
- Franco M. Luque <firstname.lastname@example.org> (francolq at github)
- Daniel Moisset <email@example.com> (dmoisset at github)