Skip to main content

Output Parsing

Output parsing is the process of extracting structured, machine-readable data from an AI model's free-form text responses. Since language models generate natural language by default, output parsing applies pattern matching, regex extraction, or schema validation to convert responses into usable data structures like JSON objects, typed fields, or database records.

Example

You ask a model to analyze a job posting and it responds in natural language. An output parser extracts specific fields: {"title": "Senior Engineer", "salary_range": "$150k-$180k", "location": "Remote", "skills": ["Python", "AWS", "Docker"]}. The parsed data flows directly into your application's database.

Related Terms

Structured OutputPrompt TemplatePrompt EngineeringLarge Language Model (LLM)

Put this into practice

Build polished, copy-ready prompts in under 60 seconds with SurePrompts.

Try SurePrompts