Specify the expected table structure
Decide whether the output should preserve visual rows and columns or produce normalized business records. Multi-level headers, merged cells, subtotals, and footnotes need explicit representation rules. A visually accurate table can still be unusable if the output loses which period or unit a number belongs to.
Link cells to their context
Keep page identifiers, table identifiers, header paths, and evidence locations when the task requires them. Include nearby notes that define units or exceptions. A cell containing 25 means little without knowing whether the column reports units sold, percentage growth, or thousands of a particular currency.
Handle spanning and repeated tables
Specify how tables continuing across pages should connect and how repeated headers should be treated. Distinguish genuine new rows from page furniture. Include both simple and difficult tables in the pilot so annotation rules are tested before the collection becomes dominated by one easy layout.
Review structure and values separately
Measure whether the model found the table, reconstructed its relationships, and extracted the correct content. Inspect errors that move values into neighboring columns even when the text itself is correct. Send Fiund examples of your desired output and the structural cases that must appear in a suitable source sample. Choose a table with a two-level header and a footnote that changes how one column should be read. Ask reviewers to reconstruct a single normalized record by hand. If they need context absent from the proposed output schema, revise the schema before treating automated cell extraction as a complete solution.
Review checklist
- Choose visual or normalized output
- Preserve header paths and units
- Define continuation and subtotal rules
- Review structure separately from cell text