I agree that for natural language processing, generalized parsing makes a lot of sense. But since Marpa's documentation and papers compared it to tools like ya

I agree that for natural language processing, generalized parsing makes a lot of sense. But since Marpa's documentation and papers compared it to tools like yacc, I analyzed it from the perspective of someone trying to parse programming languages or data formats -- the sort of thing yacc would be used for. Most generalized algorithms (such as GLR) allow you to generate and compare multiple parses. Marpa is not new in this regard. And while I agree that this is useful, it's a "run-time error", so-to-speak. Given a specific input, it can tell you the multiple parses it generated. The benefit of deterministic algorithms is that they can give you this kind of feedback at compile-time. They can generate sample input that would trigger the ambiguity, if they were seen in the wild. I think a static vs. dynamic typing comparison is apt here. A statically typed language can prove that the types are always correct. Dynamic typing defers this checking to runtime, so you don't get the same static guarantees about your program. The same sort of thing can be said of ambiguity checking in deterministic vs. generalized parsing.