Configure the env

Sulci is built on top of Django, and therefore you will need Django installed and an active project to be able to use sulci.

Also, a SQL database (we use Postgresql) is needed.

Import the trained data

Retrieve the three files of the three tables:

  1. sulci_descriptor
  2. sulci_trigger
  3. sulci_triggertodescriptor


Be careful to load at last the sulci_triggertodescriptor, as it has FK to the others.


You may have to change the table owner handly in the SQL files.

Load these three files into your database.

Install sulci

A easy way is to use pip:

pip install


A very good habit is to use a virtualenv to do so.

Or you can retrieve the code, and “python install” or put the sulci folder in your PYTHONPATH:


Then add “sulci” to your INSTALLED_APPS.

Try it from shell

Sample usage:

>>> from sulci.textmining import SemanticalTagger
>>> text = u"""«La Russie et la Chine finiront par regretter leur décision qui
             les a vues s’aligner sur un dictateur en fin de vie et qui les a
             mises en porte-à-faux avec le peuple syrien.»"""
>>> s = SemanticalTagger(text)
>>> s.descriptors
[(<Descriptor: Russie>, 100.0),
 (<Descriptor: Chine>, 100.0),
 (<Descriptor: diplomatie>, 14.798308089447328),
 (<Descriptor: Dmitri Medvedev>, 10.337552742616033)]

Test Page

A simple view is provided to easily test Sulci. You need to add the url in your urlconfs, for example:

url(r'^sulci/demo$', 'sulci.views.demo', name='sulci_demo'),

Then you’ll have to start the Django runserver and browse the page http://localhost:8000/sulci/demo.

Configure for training

If you plan to train you own Sulci or to use the command line, you have to add these settings (with you own values, of course):


Project Versions

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