KNIME Documentation

Prompt with structured output ​

Instruct a language model to return structured data directly in table columns instead of free-form text.

When this is useful ​

Structured output is useful when model responses need to be parsed, validated, or processed automatically into KNIME workflows.

Use structured output when you want to:

  • Extract structured information from text into predefined columns
  • Define the exact output schema the model should follow
  • Reliably integrate LLM output into automated or rule-based workflows
  • Extract one or multiple items from each input row

If you only need free-form text output, use a simple prompt instead.

Build a prompt with structured output ​

Prerequisites

Before you start, make sure that you have:

To prompt a model for structured output, follow these steps:

  1. Configure the LLM Prompter output format
  2. Define the output structure
  3. Configure output columns

1. Configure the LLM Prompter output format ​

Use the LLM Prompter node and configure it as follows:

  • Provide the input text column containing the prompt
  • Set Output format to Structured

This makes structured output configuration options available.

2. Define the output structure ​

In the Output Structure section, configure:

  • Target object name: A descriptive name for the items being extracted (e.g., "Actionable tasks", "Product features")
  • Target object description: Describe what should be extracted from the input text (e.g., "Tasks mentioned in the meeting that should be added to the board")
  • Target objects per input row: Determines how many items are extracted for each input row
    • Single: Extract exactly one item with the defined columns per input row
    • Multiple: Allow the model to extract one or more items with the defined structure per input row. The input columns will be duplicated for each extracted item.

3. Configure output columns ​

Define the columns that will contain the extracted data. For each column, specify:

  • Column name: The name of the output column
  • Data type: The data type (String, Integer, etc.)
  • Quantity: Whether the field is single-valued or can contain multiple values as a list
  • Description: Describe what this field should contain, including any constraints or allowed values

The model will return data structured according to these column definitions.

Example ​

See structured output in action with this complete example on KNIME Hub:

JSON

Some providers like OpenAI also support JSON as an output format. Check out this example on the Hub: Extract structured data from text.

Next steps ​

Follow this tutorial to learn how you can extract structured data with a local model using Ollama: