nltk language model (ngram) calculate the prob of a word from context

I am using Python and NLTK to build a language model as follows:

from nltk.corpus import brown
from nltk.probability import LidstoneProbDist, WittenBellProbDist
estimator = lambda fdist, bins: LidstoneProbDist(fdist, 0.2)
lm = NgramModel(3, brown.words(categories='news'), estimator)
# Thanks to miku, I fixed this problem
print lm.prob("word", ["This is a context which generates a word"])
>> 0.00493261081006
# But I got another program like this one...
print lm.prob("b", ["This is a context which generates a word"]) 

But it doesn't seem to work. The result is as follows:

>>> print lm.prob("word", "This is a context which generates a word")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.6/dist-packages/nltk/model/ngram.py", line 79, in prob
    return self._alpha(context) * self._backoff.prob(word, context[1:])
  File "/usr/local/lib/python2.6/dist-packages/nltk/model/ngram.py", line 79, in prob
    return self._alpha(context) * self._backoff.prob(word, context[1:])
  File "/usr/local/lib/python2.6/dist-packages/nltk/model/ngram.py", line 82, in prob
    "context %s" % (word, ' '.join(context)))
TypeError: not all arguments converted during string formatting

Can anyone help me out? Thanks!