To create a custom sensitive information type (SIT), the primary element must define the core pattern of the data. Since an employee ID follows a specific formatted sequence (hire date + three-digit number), a regular expression is the most precise tool to capture this pattern.

The requirement to find specific words ("Employee", "ID", or "Identification") within a 300-character proximity defines the supporting evidence. In Microsoft Purview, these specific terms are best grouped as a keyword list to provide the necessary context to increase confidence levels and reduce false positives.

Microsoft Purview Documentation: "Learn about sensitive information types," Section: Fundamental parts of a sensitive information type. This defines the primary element as the pattern (RegEx or Dictionary) and supporting evidence as proximity-based keywords.

Microsoft Purview Documentation: "Create custom sensitive information types," Step: Define the pattern. It specifies using regular expressions for fixed-length or formatted strings like IDs.

Microsoft Purview Documentation: "Sensitive information type entity definitions," Section: Supporting evidence. This explains using keyword lists to identify context within specific character proximities (default and custom ranges).

Compliance Management Standard Frameworks: Technical specifications for Pattern Matching in Data Loss Prevention (DLP), focusing on the distinction between structural patterns (RegEx) and contextual anchors (Keywords).