Grammars can be parsed from strings:
>>> from nltk import CFG >>> grammar = CFG.fromstring(""" ... 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 PCFG >>> toy_pcfg1 = PCFG.fromstring(""" ... 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 = CFG.fromstring("VP^<TOP> -> VBP NP^<VP-TOP>") >>> g.productions()[0].lhs() VP^<TOP>