I’m a longtime fan of Chris Manning and Hinrich Schutze’s “Foundations of Natural Language Processing” — I’ve learned from it, I’ve taught from it, and I still find myself thumbing through it from time to time. Last week, I wrote a blog post on SXSW titles that involved looking at n-grams of different lengths, including unigrams, bigrams, trigrams and … well, what do we call the next one up? Manning and Schutze devoted an entire paragraph to it on page 193 which I absolutely love and thought would be fun to share for those who haven’t seen it.
Before continuing with model-building, let us pause for a brief interlude on naming. The cases of n-gram language models that people usually use are for n=2,3,4, and these alternatives are usually referred to as a bigram, a trigram, and a four-gram model, respectively. Revealing this will surely be enough to…
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Well, Technically 