StarPos and EndPos for ngram log probability about berkeleylm HOT 3 CLOSED

This is be design. We actually generate the first word given START, so the 
first generation is a bigram. This is the way SRILM models things, and 
generally accepted, as far as I know. 

If the model were a 5-gram, then the first word would be generated as a bigram, 
the second as a trigram, and so on. 

Ok - thanks a lot for that info. Few questions on the design

1. Can you let me know why the loop starts from i=1, rather than i=0. 

2. Also why is it i + lm_.getLmOrder() ? Is the endPos non inclusive ? 
E.G if i is 1 and getLmOrder() is 3, startpos and endpos will be 1 and 4. If I 
am looking for tri-grams, I would have thought startpos and endpos should be 1 
and 3.

3. I am loading google books binary in my code and need only trigram log 
probabilities. Going by your explanation of using a bigram for the start of the 
sentence, should I pass 0,1 as the startpos and endpos of the first gram ? And 
then again 0,2 as the startpost and endpos of the next gram? and then follow it 
up by 1,3 ?

WOuld be grateful again for your help on this

1. The sentence already has start markers, and we don't generate start.

2. endPos is non-inclusive, you're right.

3. I'm confused why you are writing your own code? AWhat exactly is the score 
you want to compute? Why can't you just use ComputeLogProbabilityOfTextStream?