What are important factors that model-based extractors notice?

Model-based extractors are designed to leverage various contextual and positioning factors in the extraction process. The correct response highlights the significance of page position, correlation of text, and the value itself as important elements that influence the accuracy and effectiveness of data extraction.

Page position allows the extractor to understand where on the document a certain piece of information is located, which can be critical for formats like invoices or forms where data appears in predictable locations. Correlation of text is equally important as it helps in understanding the relationship between different pieces of information, enabling the extractor to discern, for example, that a number may represent an amount or a date based on its proximity to relevant keywords. The inherent value of the text itself is also crucial, as it denotes the content that needs to be extracted.

Focusing on these factors not only enhances the ability to accurately extract relevant information but also minimizes errors that might arise from isolated interpretation of data points. Other choices, while they may seem relevant, do not encompass the holistic approach model-based extractors utilize to process information effectively.