Which of the following is an example of a Rule Based Extractor?

A Rule-Based Extractor relies on predefined rules and patterns to identify and extract data from structured or semi-structured documents. The RegEx Extractor fits this description perfectly, as it utilizes regular expressions to match specific patterns in the text, enabling it to extract targeted information reliably.

In contrast, Forms AI and Neural Network Extractor are based on more advanced techniques, including machine learning and AI, to process and understand content, often using training datasets to improve their performance rather than relying on hardcoded rules. ML Extractor, similarly, employs machine learning models that are trained on large amounts of labeled data to identify and extract data, which also distinguishes it from the rule-based approach. Thus, the RegEx Extractor stands out as the appropriate example of a Rule Based Extractor.