--- title: Dialogue Analysis type: templates category: Conversational AI cat: conversational-ai order: 815 meta_title: Dialogue Analysis Data Labeling Template meta_description: Template for performing dialogue analysis for conversational AI use cases with Label Studio for your machine learning and data science projects. --- If you want to evaluate and analyze the responses present in a dialogue that already happened, and optionally correct it, use this template. Use this template to provide a section of dialogue and classify it. Annotators then provide the best response to the section of dialogue. ## Interactive Template Preview
## Labeling Configuration ```html
``` ## About the labeling configuration All labeling configurations must be wrapped in [View](/tags/view.html) tags. Use the [HyperText](/tags/hypertext.html) object tag to display dialogue data, imported in Label Studio JSON format using a key of "dialogs": ```xml ``` You can add a [header](/tags/header.html) to provide instructions to the annotator: ```xml
``` Use the [Choices](/tags/choices.html) control tag in combination with the [Choice](/tags/choice.html) tag to have annotators classify the dialogue response. Use the arguments to control how the choices appear on the interface: ```xml ``` You can change the choice `value`s to provide different classification options. Use the [TextArea](/tags/textarea.html) control tag to provide annotators with a free text box to supply their own response to the dialogue. Add the `editable=true` argument to allow them to edit their answer, or `required=true` to force annotators to supply an alternate response: ```xml ``` ## Related tags - [HyperText](/tags/hypertext.html) - [Choices](/tags/choices.html) - [TextArea](/tags/textarea.html)