For Beamery users with AI functionality enabled, an automatic parsing of the Vacancy's job description will kick off their Vacancy's Calibration. The Job Description Parser uses the Beamery Knowledge Graph to analyze the full text of the job description (responsibilities, requirements, qualifications) for role and skill inference, rather than the job title alone. This allows for accurate matching even with messy or unclear job titles. The parser maps to standardized roles and skills on the Beamery Knowledge Graph to improve AI Talent Match quality. 

Types of Automatic Calibration

A Vacancy will have one of several labels to indicate which type of calibration has taken place. These labels include: 

Auto-Calibrated from Job Description

This vacancy has been automatically calibrated to the Vacancy's Job Description.

Auto-Calibrated from Beamery's Taxonomy

This vacancy has been auto-calibrated based on the Job Role inferred from the Vacancy Title. This is for vacancies created manually without a Job Description or for organizations that do not have an integrated ATS that includes Job Description in the data sync. 

Manually Edited from Job Description Calibration

This is for vacancies that were originally auto-calibrated to the Job Description but have since been manually edited by a user. 

Manually Edited from Beamery's Taxonomy

This is for vacancies that were originally auto-calibrated based on the Job Role inferred from the Vacancy Title but have since been manually edited by a user. 

Updating the Job Description will not trigger another parsing.