Ask HN: Natural language processing to identify grammar in a text?

Maybe you can give GPT-3 a try.

If you want to go the custom route, the easy way but which consume a lot of processing power, is to use a neural network and necessitate a boring dataset phase construction.

You build a dataset corresponding to your problem. And you learn it with the neural network.

For inspiration you can see my colorify browser extension, which uses a neural network to learn at the same time to split sentences, predict POS tags, predict root of the sentence, predict the parse tree which are then used to decorate the webpage.

What I did was just programmatically build a dataset from the spacy parser to build a custom javascript parser which does what I want. If I wanted to add some additional information that Spacy doesn't provide like grammar tenses and features, I can complete my dataset manually and have the network predict all the decorations at the same time, which allows it to not need a lot of samples because the layers are shared.

You can probably build your dataset faster by interacting with your neural network (active learning).

For the model you can start with something simple like a convolution residual network architecture. And later use some transformers when you want to reach state of the art.

[0]: http://www.hemingwayapp.com/