---
title: "Validate Definitions"
slug: "validate-definitions"
updated: 2025-10-15T17:39:58Z
published: 2025-10-15T17:39:58Z
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.revealdata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Validate Definitions

## Overview

**Validation**is an important stage in aji’s review process because it takes your Definition—which was refined using a small dataset during Calibration—and tests its accuracy on a larger random set of documents from your dataset. While this step is optional and you can move from a Calibration Review directly to a GenAI or Hybrid GenAI Review, Validation can help you see how your Definition performs against a large number of documents for quality assurance purposes.

> [!NOTE]
> **Note**
> 
> In Reveal, there is no explicit “Validation” modal to fill that validates your dataset. Instead, you will perform a Calibration Review on a sample set of random documents.

Validation is performed by following the below steps:

1. **Create Your Random Set**– Create a sample set of random documents, sourced from your whole target data population.
2. **Start a Calibration Review**– Execute a Calibration Review on your random set.
3. **Review Your Random Set** – Code all of the documents in your random set.
4. **Apply Validation Findings** – View your Validation results and determine next steps.

## I. Create Your Random Set

> [!WARNING]
> **Important**
> 
> When sampling documents using the below instructions from your target data population, keep in mind that Reveal may pick up documents that have already been rated through a previous Calibration Review.

1. In the Review Grid, **find your work folder** that contains your target data population (described in our [aji Environment and Data Requirements](/reveal/docs/aji-environment-and-data-requirements#dataset-criteria-prep) article).
2. **Click** **the work folder** to create a new pill in the search bar.
3. Click **Sample** in the Review Grid toolbar, and fill out the modal as described in [Create a Sample Document Set](/reveal/docs/create-a-sample-document-set).
  1. **Copy the samples** **into** **a folder**, and give that work folder a name that makes sense to you and can be easily referenced later.

> [!NOTE]
> **Note**
> 
> Larger random sets will provide more accurate results against your target data population.

## II. Start a Calibration Review

1. **Fill out** the Create Calibration Review modal to start a new Calibration Review. Instructions on this modal can be found in our [Calibrate aji](/reveal/docs/calibrate-aji#run-a-calibration-test-modal) article.
  1. When selecting **Documents to Review**, make sure to choose *Create a New Document Selection*, then find your random set work folder.

## III. Review Your Random Set

1. In the Review Grid, **find your** **random set** work folder.
2. **Code** all of the documents in your random set.
  - Make sure you’re using the right AI Tag associated with your Calibration Review, which can be found in the *Calibration Results* tab (see [Calibrate aji](/reveal/docs/calibrate-aji#ii-code-documents) for more information).

## IV. Apply Validation Findings

1. Using the Calibration Review data visualizations, **interpret your Validation results**. The Calibration Review data visualizations are discussed in detail in our [Calibrate aji](/reveal/docs/calibrate-aji#calibration-results-tab) article.
  1. Pay close attention to the **Evaluation**pane, which contains the Agreement Rate and true / false agreement outcomes.
  2. You can also **calculate Precision**, **Recall**, and **F1** for more insight into your Validation results.
2. **Decide** **next steps**.
  - If you are happy with your Agreement Rate, proceed to either running a **GenAI Review** or **Hybrid GenAI Review**.
  - If you think your Agreement Rate can be improved, **return to the** **Define stage**, then:
    - Edit your Definition.
    - Perform Calibration Reviews until you reach an optimal Agreement Rate.
    - Validate your Definition (optional).