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testthirdware
Helper I
Helper I

AI Builder model does not detect a table in PDF while building a model

Hi,

 

I am building a model to extract a table with 5 columns, after i add a collection with the pdf files which has the exact table data with same 5 columns in the PDF, it doesn't get detected as a table. instead i had to manually select each row of the table and also for each column.

 

Note: Earlier i built a model for the same collection to extract the table values, it detected. But after a week it doesn't work. 

screenshot taken earlier, But now this is not detecting as below: 

testthirdware_1-1617893119405.png

 

Kindly suggest

 

Thanks

 

1 ACCEPTED SOLUTION

Accepted Solutions
JoeF-MSFT
Power Apps
Power Apps

Hi @testthirdware,


Thanks for posting this question.

 

Indeed, the table tagging experience in Form Processing has changed this week. Check out the recent blog post about this: Improved table extraction in AI Builder form processing | Power Automate Blog (microsoft.com)


By providing a way to tag cell by cell, tables that couldn’t be detected previously by the model can now be extracted. It also gives the flexibility to tag more complex cases like tables with nested items in rows.

 

For models trained until last week, the old experience can still be used. But for new models this is the new table tagging experience. Indeed, for what seems to be your case, some tables can now take more time to tag. The good news is that we continue working on improving the tagging experience to make it much faster to tag large tables.

 

I hope this clarifies.

View solution in original post

2 REPLIES 2
JoeF-MSFT
Power Apps
Power Apps

Hi @testthirdware,


Thanks for posting this question.

 

Indeed, the table tagging experience in Form Processing has changed this week. Check out the recent blog post about this: Improved table extraction in AI Builder form processing | Power Automate Blog (microsoft.com)


By providing a way to tag cell by cell, tables that couldn’t be detected previously by the model can now be extracted. It also gives the flexibility to tag more complex cases like tables with nested items in rows.

 

For models trained until last week, the old experience can still be used. But for new models this is the new table tagging experience. Indeed, for what seems to be your case, some tables can now take more time to tag. The good news is that we continue working on improving the tagging experience to make it much faster to tag large tables.

 

I hope this clarifies.

View solution in original post

Thanks for the info.

 

Regards,

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