Classifying documents

Classifying Documents with Semaphore

Semaphore enables organizations to automatically classify and enrich content using a powerful, transparent, and governed rule-based engine. This process transforms unstructured documents into structured, semantically tagged assets that can be searched, routed, analyzed, and trusted across the enterprise.

At the heart of this capability is Semaphore's Classification and Language Services (CLS) module, which applies semantic models and classification rules to content in real time or batch mode. This allows organizations to scale intelligent automation, improve metadata consistency, and support AI readiness.

Rule-Based Classification: Transparent and Deterministic

Semaphore uses deterministic, rule-based logic to classify content. Unlike opaque machine learning models, these rules are authored by information architects and subject matter experts, and are:

• Explainable: Each classification decision can be traced back to a specific rule.

• Governed: Rules are version-controlled and reviewed before deployment.

• Multilingual: Rules can be written and executed in multiple languages using language packs.

Example:

A rule might state:

"If a document contains the phrase 'termination clause' within 10 words of 'employment contract', classify it as 'Contractual Obligation'."

These rules are grouped into rule classes and deployed via configuration sets, which define how classification is executed for different content types, languages, or business units.