# How to extract ngrams from ambigous text after lemmatization?

After lemmatization of text I have a sequence of sets of lemmas, because every word can correspond to more than one lemma. How should I extract ngram statistics based on that? The only thing that comes to mind is counting every possible combination, but this seems a bit weird. Is there any other option?

More implementation-related question: is there a way to do this by NLTK?

In the end, you will probably use these frequencies to estimate the probability p(around | I, walk). To translate this to the space of lexemes, you must again sum over all possible lexemes for these words: $$p(\mbox{around} \mid \mbox{I}, \mbox{walk}) = \sum_{i,j,k} p(\mbox{around}_i \mid \mbox{I}_j, \mbox{walk}_k)$$