iepy 0.9.6

Features

• A corpus annotation tool with a web-based UI

• An active learning relation extraction tool pre-configured with convenient defaults.

• A rule based relation extraction tool 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

• An easily hack-able active learning core, ideal for scientist wanting to experiment with new algorithms.

Installation

Install the required packages:

sudo apt-get install build-essential python3-dev liblapack-dev libatlas-dev gfortran openjdk-7-jre

Then simply install with pip:

pip install iepy

Full details about the installation is available on the Read the Docs page.

Running the tests

If you are contributing to the project and want to run the tests, all you have to do is:

• Make sure your JAVAHOME is correctly set. Read more about it here

• In the root of the project run nosetests

Learn more

The full documentation is available on Read the Docs.

Authors

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

• Rafael Carrascosa <rcarrascosa@machinalis.com> (rafacarrascosa at github)

• Javier Mansilla <jmansilla@machinalis.com> (jmansilla at github)

• Gonzalo García Berrotarán <ggarcia@machinalis.com> (j0hn at github)

• Franco M. Luque <francolq@famaf.unc.edu.ar> (francolq at github)

• Daniel Moisset <dmoisset@machinalis.com> (dmoisset at github)

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

You can join the mailing list here