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- IEPY
- ====
- IEPY is an open source tool for
- `Information Extraction <http://en.wikipedia.org/wiki/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 <http://iepy.readthedocs.org/en/latest/active_learning_tutorial.html>`_
- needing to perform Information Extraction on a large dataset.
- - `scientists <http://iepy.readthedocs.org/en/latest/how_to_hack.html>`_
- wanting to experiment with new IE algorithms.
- Features
- --------
- - `A corpus annotation tool <http://iepy.readthedocs.org/en/latest/corpus_labeling.html>`_
- with a `web-based UI <http://iepy.readthedocs.org/en/latest/corpus_labeling.html#document-based-labeling>`_
- - `An active learning relation extraction tool <http://iepy.readthedocs.org/en/latest/active_learning_tutorial.html>`_
- pre-configured with convenient defaults.
- - `A rule based relation extraction tool <http://iepy.readthedocs.org/en/latest/rules_tutorial.html>`_
- 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 <http://nlp.stanford.edu/software/corenlp.shtml>`_
- - `An easily hack-able active learning core <http://iepy.readthedocs.org/en/latest/how_to_hack.html>`_,
- ideal for scientist wanting to experiment with new algorithms.
- Installation
- ------------
- Install the required packages:
- .. code-block:: bash
- sudo apt-get install build-essential python3-dev liblapack-dev libatlas-dev gfortran openjdk-7-jre
- Then simply install with **pip**:
- .. code-block:: bash
- pip install iepy
- Full details about the installation is available on the
- `Read the Docs <http://iepy.readthedocs.org/en/latest/installation.html>`__ 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 <http://iepy.readthedocs.io/en/latest/installation.html#install-iepy-package>`_
- - In the root of the project run `nosetests`
- Learn more
- ----------
- The full documentation is available on `Read the Docs <http://iepy.readthedocs.org/en/latest/>`__.
- Authors
- -------
- IEPY is © 2014 `Machinalis <http://www.machinalis.com/>`_ in collaboration
- with the `NLP Group at UNC-FaMAF <http://pln.famaf.unc.edu.ar/>`_. 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 <https://groups.google.com/forum/?hl=es-419#%21forum/iepy>`__
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