Let me rephrase the debate, in a way that can hopefully clarify the main point of contention: C: Your statistical models are woefully inadequate at describing

Let me rephrase the debate, in a way that can hopefully clarify the main point of contention: C: Your statistical models are woefully inadequate at describing language. N: That inadequacy is related particularly to Markov models and Ngram models. More sophisticated statistical models will be adequate. C: Then why haven't you built the more sophisticated models? Why are you still using Markov models and Ngrams? N: Those work well enough for engineering applications. The attitude of "it works well enough for engineering" is what Chomsky is actually criticizing. And that criticism is entirely valid: an empirical scientist would never claim that a theory is true because it can be used in engineering. It's funny to me that Norvig holds up the PCFG as an example of a new and improved statistical model of language. The PCFG is actually terrible in many ways, the most obvious of which is that it doesn't take into account the Theta Criterion [1], one of the most fundamental phenomena of language. An example of this rule is that a noun phrase can only have one determiner. This restriction is so strong that it will never be violated in any kind of professionally composed text. But it is very awkward to try to encode this rule in a PCFG (you essentially have to split the NP symbol into DetNP vs UndetNP). I wrote a blog post describing the problems of the PCFG formalism: https://ozoraresearch.wordpress.com/2017/03/17/chuckling-a-bit-at-microsoft-and-the-pcfg-formalism/ https://ozoraresearch.wordpress.com/2017/03/17/chuckling-a-b... [1]: https://en.wikipedia.org/wiki/Theta_criterion https://en.wikipedia.org/wiki/Theta_criterion