01
Where this one gets misread
Tables are where document AI most often fails quietly. Merged cells, headers that repeat across pages and totals rows produce output that is well-formed, plausible and wrong.
Glossary
What is table extraction?
Table extraction turns a table into rows, columns and cells. Merged cells, headers that repeat across pages and nested layouts are where it usually breaks.
By Marella AI · Updated 21 Aug 2026
02
Questions to ask
Ask for a worked example on your own material, and the evidence needed to reproduce it.
- What happens to a merged-cell table, and to one that spans pages?
- How is a header row identified?
- What happens to footnotes and units?
- How is a failed extraction flagged rather than guessed?
03
How Marella uses the term
We use “Table extraction” only where a product mechanism or an evaluation method backs it up, and we say when the behaviour depends on how a deployment is configured.
- Backed by a product mechanism or an evaluation method
- Deployment differences flagged
Caveats
- B1A definition is not a claim about how the product performs.
- B2Vendor implementations vary.
- B3Test the term against a representative workflow.
Related pages
Test it on your own documents
Pick a real piece of work, agree what a good answer looks like, then go through the results together.