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It is interesting that the fundamental parts of grammar checking are still driven by rules engines and GOFAI expert systems. Even the gramamarly core is written
by melony 5y ago
It is interesting that the fundamental parts of grammar checking are still driven by rules engines and GOFAI expert systems. Even the gramamarly core is written in common lisp as a GOFAI app. Most of the modern attention/transformer NLPs are used to supplement the front end tasks like dependency parsing.
- solarmist 5y agoI'm not sure I believe this represents state of the art in this area. I think they just have put enough hours into writing rules it does a passable job for the biggest languages it supports. If you get enough rules it can look like progress. I looked at the engine for the Japanese parsing and it looks like they are parsing Japanese in fundamentally the same way they are English and it's has been known for around 20 years that is insufficient. Japanese requires tagging be done in order to tokenize it not the reverse as is done with English. Take a look at spaCy if you're interested in what's possible nowadays, but it's not an end user product. Edit: it's not quite that bad they're using GoSen which stopped being used only about 10 years ago.
- itazula 5y agoYes, I put in Japanese that was nonsense, and it passed with flying colors.
- solarmist 5y agoYeah, I figured. That's why there are almost no NLP tools on the market that support Asian languages, in particular Japanese, Korean, and somewhat Chinese (Chinese is its own thing because of the large number of engineers it has to throw at problems).
- lewisjoe 5y agoI'm part of the team that makes Zoho Writer's grammar checker[1] and we did go with a modern neural-net based NLP technique to detect grammatical errors. It had a huge win in terms of the number of errors it caught, but we could never tell the user what exactly is wrong with that sentence, because.. well, deep learning. So we've taken a hybrid approach where a modern AI flags errors and then run it through a rule engine to try and figure out what exactly is wrong. This way we get the best of both worlds. That lack of explanation is also why Grammarly is sticking with GOFAI systems perhaps. But the future of this problem area is certainly AI augmented with rule engines. [1] - https://www.zoho.com/writer/free-grammar-checker.html https://www.zoho.com/writer/free-grammar-checker.html
- melony 5y agoBut if the NLP is able to flag more errors than the rules engine, how could the rules engine explain the errors?
- solarmist 5y agoI'm not sure I understand what you're asking, but neural net-based NLP can't explain itself while the rules engines just use simple pattern matching techniques, so it can.
- melony 5y agoOP is saying that the rules engine can't catch a bunch of errors that the ML based NLP can. In other words the ML system has a bigger input domain than the rules engine. I am confused about how they plan to use the rules engine to explain errors that it won't be able to catch at all.
- solarmist 5y agoOh, I expect that you'd use NN NLP to do accurate parsing/tagging/NER then write rules based on the output of that parsing. If you look at https://explosion.ai/demos/displacy https://explosion.ai/demos/displacy, you can see the high-level information you can extract from sentences nowadays, which better matches our understanding of how grammar rules work. And that's an approach that does generalize to languages like Japanese.
- solarmist 5y agoYes, that's currently the problem. I'll be that Grammarly is doing something similar itself. Do you support Japanese or other East Asian languages?
- vfulco2 5y agoBoy, I would love to see an API for the analytical tools.