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Information Extraction framework in Python

Project description

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.

Features

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:

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:

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

You can join the mailing list here

Project details


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iepy-0.9.6.tar.gz (554.0 kB view hashes)

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