nltk_tgrep 1.0.6

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

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.