# Jurafsky and Martin (2018) Do not understand formula in naiye bayes classifier

Currently I am reading Language and Speech Processing by , Chapter 4 Naiye Bayes and Sentiment Classification. At page $$7,$$ when the authors discuss worked example. Data set is as follows:

Training set: just plain boring (-)

entirely predictable and lacks energy (-)

no surprises and very few laughs (-)

very powerful (+)

the most fun film of the summer (+)

Test predictable with no fun (?)

I fail to understand why is $$20$$ added in the denominator, i.e. $$P( \text{'prediction'} | -) = \frac{1+1}{14+20}.$$

If you look at equation (4.14) on page 6, you see that 20 is actually $$|V|$$ that is the total number of words in the vocabulary.