================================= tgrep2 Searching for NLTK Trees

TGrep search implementation for NLTK_ trees.

.. _NLTK: http://www.nltk.org

Copyright (c) 16 March, 2013 Will Roberts [email protected].

Licensed under the MIT License (see source file tgrep.py for details).

This module supports TGrep2 syntax for matching parts of NLTK_ Trees. Note that many tgrep operators implemented here require the tree passed to be a ParentedTree.

NOTE: nltk_tgrep has been integrated into the NLTK_ project, and can now be found here at its new home_. This github repository will remain here, but will not be updated in future.

.. _its new home: https://github.com/nltk/nltk/blob/develop/nltk/tgrep.py

Tgrep tutorial: http://www.stanford.edu/dept/linguistics/corpora/cas-tut-tgrep.html

Tgrep2 manual: http://tedlab.mit.edu/~dr/Tgrep2/tgrep2.pdf

Tgrep2 source: http://tedlab.mit.edu/~dr/Tgrep2/

.. image:: https://travis-ci.org/wroberts/nltk_tgrep.svg?branch=master :target: https://travis-ci.org/wroberts/nltk_tgrep :alt: Travis CI build status

.. image:: https://coveralls.io/repos/wroberts/nltk_tgrep/badge.svg?branch=master :target: https://coveralls.io/r/wroberts/nltk_tgrep?branch=master :alt: Test code coverage

.. image:: https://img.shields.io/pypi/v/nltk_tgrep.svg :target: https://pypi.python.org/pypi/nltk_tgrep/ :alt: Latest Version

Requirements:

• Python 2.6 or better, or Python 3.2 or better
• future_ (for Python 2)
• NLTK_, version 3.0.0 or better
• pyparsing

::

$ sudo pip install nltk_tgrep

.. _future: http://python-future.org

Usage:

::

>>> from nltk.tree import ParentedTree
>>> import nltk_tgrep
>>> tree = ParentedTree.fromstring('(S (NP (DT the) (JJ big) (NN dog)) (VP bit) (NP (DT a) (NN cat)))')
>>> nltk_tgrep.tgrep_nodes(tree, 'NN')
[ParentedTree('NN', ['dog']), ParentedTree('NN', ['cat'])]
>>> nltk_tgrep.tgrep_positions(tree, 'NN')
[(0, 2), (2, 1)]
>>> nltk_tgrep.tgrep_nodes(tree, 'DT')
[ParentedTree('DT', ['the']), ParentedTree('DT', ['a'])]
>>> nltk_tgrep.tgrep_nodes(tree, 'DT $ JJ')
[ParentedTree('DT', ['the'])]

This implementation adds syntax to select nodes based on their NLTK_ tree position. This syntax is N plus a Python tuple representing the tree position. For instance, N(), N(0,), N(0,0) are valid node selectors. Example::

>>> tree = ParentedTree.fromstring('(S (NP (DT the) (JJ big) (NN dog)) (VP bit) (NP (DT a) (NN cat)))')
>>> tree[0,0]
ParentedTree('DT', ['the'])
>>> tree[0,0].treeposition()
(0, 0)
>>> nltk_tgrep.tgrep_nodes(tree, 'N(0,0)')
[ParentedTree('DT', ['the'])]

Caveats:

• Link modifiers: "?" and "=" are not implemented.
• Tgrep compatibility: Using "@" for "!", "{" for "<", "}" for ">" are not implemented.
• The "=" and "~" links are not implemented.

Known Issues:

• There are some issues with link relations involving leaf nodes (which are represented as bare strings in NLTK_ trees). For instance, consider the tree::

  (S (A x))
  

  The search string * !>> S should select all nodes which are not dominated in some way by an S node (i.e., all nodes which are not descendants of an S). Clearly, in this tree, the only node which fulfills this criterion is the top node (since it is not dominated by anything). However, the code here will find both the top node and the leaf node x. This is because we cannot recover the parent of the leaf, since it is stored as a bare string.

  A possible workaround, when performing this kind of search, would be to filter out all leaf nodes.