removed ngram model package, pending resolution of issues nltk#133, n…

…ltk#157, nltk#167, nltk#367, nltk#380, nltk#388, nltk#396, nltk#602, nltk#603; package saved in a new branch

nltk/__init__.py

@@ -125,7 +125,6 @@
 from nltk.classify import *
 from nltk.inference import *
 from nltk.metrics import *
-from nltk.model import *
 from nltk.parse import *
 from nltk.tag import *
 from nltk.tokenize import *
@@ -172,7 +171,7 @@
 
 from nltk import align, ccg, chunk, classify, collocations
 from nltk import data, featstruct, grammar, inference, metrics
-from nltk import misc, model, parse, probability, sem, stem
+from nltk import misc, parse, probability, sem, stem
 from nltk import tag, text, tokenize, tree, treetransforms, util
 
 # override any accidentally imported demo

nltk/text.py

@@ -24,7 +24,6 @@
 from nltk.probability import FreqDist, LidstoneProbDist
 from nltk.probability import ConditionalFreqDist as CFD
 from nltk.util import tokenwrap, LazyConcatenation
-from nltk.model import NgramModel
 from nltk.metrics import f_measure, BigramAssocMeasures
 from nltk.collocations import BigramCollocationFinder
 from nltk.compat import python_2_unicode_compatible, text_type
@@ -375,21 +374,6 @@ def readability(self, method):
         # code from nltk_contrib.readability
         raise NotImplementedError
 
-    def generate(self, length=100):
-        """
-        Print random text, generated using a trigram language model.
-
-        :param length: The length of text to generate (default=100)
-        :type length: int
-        :seealso: NgramModel
-        """
-        if '_trigram_model' not in self.__dict__:
-            print("Building ngram index...")
-            estimator = lambda fdist, bins: LidstoneProbDist(fdist, 0.2)
-            self._trigram_model = NgramModel(3, self, estimator=estimator)
-        text = self._trigram_model.generate(length)
-        print(tokenwrap(text))
-
     def similar(self, word, num=20):
         """
         Distributional similarity: find other words which appear in the