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Installing and using RstMarcuTree
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Introduction
============

This library helps you to process a Rhetorical Structure Theory Discourse Tree

It returns a RSTTree representing the tree composed by RSTNode.
The tree is enriched with attribute like promotion set described by Daniel Marcu in paper:

* Building up rhetorical structure tree 1996

* Discourse trees are good indicators of importance in test 1999


Installation
============

RstMarcuTree has support for python 2.7

dependencies: discoursegraphs

$ pip2.7 install rstmarcutree

Usage
=====

The library process a file containing a rst tree in .dis format.
You can use online discourse dependency parser like feng hirst 2014 parser to produce
a discourse tree of a text.

Vanessa Wei Feng and Graeme Hirst, 2014.
A Linear-Time Bottom-Up Discourse Parser with Constraints and Post-Editing.

Vanessa Wei Feng and Graeme Hirst, 2014.
Two-pass Discourse Segmentation with Pairing and Global Features.

You can use:
    https://github.com/NLPbox/rst-converter-service
to easily convert the file in .dis output:

having ./test_rst.dis file path in python2.7 console or script you can just just:

>>> from rstmarcutree import load_tree
>>>
>>> rst_tree = load_tree('./test_rst.dis')
>>>
>>> root = rst_tree.get_node_by_index(0)
>>>
>>> root_satellite = root.get_satellite()

To get the saliency score of terminal nodes between 0 and 1:

>>> edus = tree.get_edus()
>>> for edu in edus:
>>>     print edu.get_saliency_score()

Test
====

If you directly clone the repository, supposed you have already installed 
rstmarcutree, you can test it with:

$ cd tests
$ python test_marcu_classes.py
$ python test_saliency_score.py

Contact
========

For help or if you find any bug write to [email protected]