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@pcyin Hi, I have two questions about the spider experiments.
In text2sql for DB with multiple tables, we will also need representation for each table other than columns. In the paper you mentioned the table representation is obtained via the prefix [CLS] token, do you consider the table name in this step? Right now the input to tabert does not have the table name/caption part, but did you concatenate the table name and column name? Otherwise, it seems hard to differentiate columns in different tables with the same name, e.g., name column in tables actor and director.
For the [CLS] representation, is it part of the context_encoding returned by the model as shown in the example? Seems the [CLS] token is considered as part of the context.
It would be very helpful if you could help clarify this. Thanks!
The text was updated successfully, but these errors were encountered:
@pcyin Hi, I have two questions about the spider experiments.
In text2sql for DB with multiple tables, we will also need representation for each table other than columns. In the paper you mentioned the table representation is obtained via the prefix [CLS] token, do you consider the table name in this step? Right now the input to tabert does not have the table name/caption part, but did you concatenate the table name and column name? Otherwise, it seems hard to differentiate columns in different tables with the same name, e.g.,
name
column in tablesactor
anddirector
.For the [CLS] representation, is it part of the
context_encoding
returned by the model as shown in the example? Seems the [CLS] token is considered as part of the context.It would be very helpful if you could help clarify this. Thanks!
The text was updated successfully, but these errors were encountered: