Schema Modeling about rat-sql

[rafiip]

I believe you are confused about the concept of unseen schema. The database schema is always known to the model, Whether you are in the training or testing phase. The model's schema during the testing phase is not seen before, meaning internal relations and/or tokens are a novelty to the model. This does not mean that the model cannot encode them.

[manzambi11]

I didn't see this hypothesis even in the article that the schema is always known in the model.

In the article, the challenge in Text to SQL is to jointly encode the question and schema to optimize the generalization for the model be able to have a high accuracy even in unseen schema.

I can use the pretrained RAT with my own dataset. How my schema will be encoded? Because column and table names in database are not often in natural language. For : t_name (is not a NL) for name.

So how RAT handle this problem?

[manzambi11]

I think This ticket can be closed. After reading, I understand that BERT can handle UNKNOW words by splitting words into characters, so any words will have an embedding vector