When you tell your employment story, AI can now identify who did what, to whom, and why by analyzing the underlying structure of your sentences. This matters because it helps systems understand whether you were taking initiative or responding to circumstances—a meaningful distinction employers care about but don't always ask directly.
Semantic role labeling is a natural language processing technique that identifies who did what to whom in a sentence, assigning roles like agent, action, and outcome to each part of your employment story.
For people with reentry challenges, AI uses this technique to restructure how your work history reads, ensuring your contributions and achievements are grammatically and logically foregrounded rather than buried under passive or evasive language that raises flags with hiring managers.
Peri can explain this concept, give practical examples, help you decide whether it applies to your situation, or recommend a journey if appropriate.
Explore related journeys or tell Peri what you're working through.