.. Copyright (C) 2001-2012 NLTK Project
.. For license information, see LICENSE.TXT

===============
Grammar Parsing
===============

Grammars can be parsed from strings:

    >>> from nltk import parse_cfg
    >>> grammar = parse_cfg("""
    ... S -> NP VP
    ... PP -> P NP
    ... NP -> Det N | NP PP
    ... VP -> V NP | VP PP
    ... Det -> 'a' | 'the'
    ... N -> 'dog' | 'cat'
    ... V -> 'chased' | 'sat'
    ... P -> 'on' | 'in'
    ... """)
    >>> grammar
    <Grammar with 14 productions>
    >>> grammar.start()
    S
    >>> grammar.productions() # doctest: +NORMALIZE_WHITESPACE
    [S -> NP VP, PP -> P NP, NP -> Det N, NP -> NP PP, VP -> V NP, VP -> VP PP,
    Det -> 'a', Det -> 'the', N -> 'dog', N -> 'cat', V -> 'chased', V -> 'sat',
    P -> 'on', P -> 'in']

Probabilistic CFGs:
   
    >>> from nltk import parse_pcfg
    >>> toy_pcfg1 = parse_pcfg("""
    ... S -> NP VP [1.0]
    ... NP -> Det N [0.5] | NP PP [0.25] | 'John' [0.1] | 'I' [0.15]
    ... Det -> 'the' [0.8] | 'my' [0.2]
    ... N -> 'man' [0.5] | 'telescope' [0.5]
    ... VP -> VP PP [0.1] | V NP [0.7] | V [0.2]
    ... V -> 'ate' [0.35] | 'saw' [0.65]
    ... PP -> P NP [1.0]
    ... P -> 'with' [0.61] | 'under' [0.39]
    ... """)

Chomsky Normal Form grammar (Test for bug 474)

    >>> g = parse_cfg("VP^<TOP> -> VBP NP^<VP-TOP>")
    >>> g.productions()[0].lhs()
    VP^<TOP>
