What information does the Extraction Confidence score provide?

The Extraction Confidence score is crucial as it quantifies the system's confidence in its ability to accurately identify and extract specific fields or tables from a document. This score usually ranges from 0 to 1, with higher values indicating a greater degree of certainty that the extracted data corresponds correctly to the intended fields.

For instance, if a document processing system is designed to extract specific entities such as names, dates, or monetary amounts, the Extraction Confidence score will reflect how precise the extraction was based on the algorithms used and the model's training data. A high confidence score would suggest that the extracted information is likely to be correct, which is vital for processes that rely on accurate data transcription and interpretation from various document types.

In contrast, while recognition of document headers, accuracy of character recognition, and overall classification accuracy are relevant aspects of document processing, they do not directly relate to the Extraction Confidence score specifically, which focuses on the precision of field and table extraction.