Option A is incorrect. The 'ocrScore' in the '_documentMetadata' field specifies the confidence score for the optical character recognition (OCR) 'process' for that document, not the confidence of specific extracted values. The 'score' field associated with individual extracted values indicates confidence for that specific value. Option B is correct. Document AI models can return lists, and the 'invoice_itemS field is given as an example. The JSON format for 'invoice_items' shows an array of objects for multiple items. The order is inherently maintained in such list extractions. Option C is correct. The sources explicitly state that in table extraction, the values in the JSON output are provided in the same order as the rows in the table, which allows columns to be easily joined. This ensures the structural integrity of the extracted table data. Option D is incorrect. For question optimization, it is crucial to be specific and precise. The guidelines advise against asking generic questions like 'What is the date?' without including more details, especially when multiple similar values might be present, as Document AI is not expected to guess intentions or have extended domain knowledge. Option E is incorrect. If the Document AI model does not find an answer (such as it does not return a 'value' key at all within that field, although it does return the 'score' key to indicate its confidence that the answer is not present.