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” relation.

It’s aimed at:
  • users needing to perform Information Extraction on a large dataset.
  • scientists wanting to experiment with new IE algorithms.

You can follow the development of this project and report issues at http://github.com/machinalis/iepy or join the mailing list here




IEPY is © 2014 Machinalis in collaboration with the NLP Group at UNC-FaMAF. Its primary authors are:


  • Fixed some dependencies declarations to provide support for python 3.5
  • Bug fix respect to active learning predictions
  • Added support for German preprocess (thanks @sweh)
  • Added multicore preprocess
  • Added support for Stanford 3.5.2 preprocess models
  • Added grammatical parsing to the preprocess flow of documents
  • Added support for Spanish preprocess
  • Restricted each iepy-instance to a single language
  • Gazetter support
  • Labeling UI improvements
  • Performance and memory usage improvements
  • Model simplifications (labels, metadata)
  • Storage & view of predictions
  • Add entity kind on the modal dialog
  • Change arrows display to be more understandable
  • Join skip and don’t know label options
  • Change options dropdown for radio buttons
  • Show help for shortcuts and change the order of the options
  • Documents rich view (without needing to be labeling the document for some relation)
  • instance upgrader