NLTK Context Free Grammar Genaration

Question

I'm working on a non-English parser with Unicode characters. For that, I decided to use NLTK.

But it requires a predefined context-free grammar as below:

  S -> NP VP
  VP -> V NP | V NP PP
  PP -> P NP
  V -> "saw" | "ate" | "walked"
  NP -> "John" | "Mary" | "Bob" | Det N | Det N PP
  Det -> "a" | "an" | "the" | "my"
  N -> "man" | "dog" | "cat" | "telescope" | "park"
  P -> "in" | "on" | "by" | "with" 

In my app, I am supposed to minimize hard coding with the use of a rule-based grammar. For example, I can assume any word ending with -ed or -ing as a verb. So it should work for any given context.

How can I feed such grammar rules to NLTK? Or generate them dynamically using Finite State Machine?

Answer 1

Maybe you're looking for CFG.fromstring() (formerly parse_cfg())?

From Chapter 7 of the NLTK book (updated to NLTK 3.0):

> grammar = nltk.CFG.fromstring("""
 S -> NP VP
 VP -> V NP | V NP PP
 V -> "saw" | "ate"
 NP -> "John" | "Mary" | "Bob" | Det N | Det N PP
 Det -> "a" | "an" | "the" | "my"
 N -> "dog" | "cat" | "cookie" | "park"
 PP -> P NP
 P -> "in" | "on" | "by" | "with"
 """)

> sent = "Mary saw Bob".split()
> rd_parser = nltk.RecursiveDescentParser(grammar)
> for p in rd_parser.parse(sent):
      print p
(S (NP Mary) (VP (V saw) (NP Bob)))