task_categories:text-classification language:en size_categories:1K<n<10K format:csv modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
task_categories:
- text-classification
language:
- en
size_categories:
- 1K<n<10K
---


# Dataset: Core Intents

The **Core Intents** dataset contains feedback-related utterances classified into seven key categories. This dataset is designed to help train voice assistants in handling fundamental types of feedback and adjusting their behavior accordingly.

## Labels

The dataset includes the following labels:
- **ask_clarify**: Requests for clarification, where the user seeks clearer explanations.
- **ask_confirmation**: Requests for confirmation, where the user asks to validate a previous command or statement.
- **ask_repeat**: Requests for repetition, where the user asks for something to be repeated.
- **negative_feedback**: Negative responses or corrections, indicating dissatisfaction or disagreement.
- **positive_feedback**: Positive responses, expressing satisfaction or agreement.
- **neutral_feedback**: Neutral responses, where the user shows indifference or general acceptance.
- **stop**: Commands indicating the user wants to halt an action or process.

## Examples

Sample utterances for each label:

- **ask_clarify**: 
  - "your response was not clear"
  - "your words were not so clear to me"

- **ask_confirmation**: 
  - "can you check and confirm my last command please"
  - "can you check and confirm it"

- **ask_repeat**: 
  - "would you try again please"
  - "would you try what you said again"

- **negative_feedback**: 
  - "command wrong"
  - "dammit, I did not say it"

- **positive_feedback**: 
  - "thanks, that's amazing"
  - "that is excellent, much appreciated"

- **neutral_feedback**: 
  - "anything is fine"
  - "any one would be good to me"

## Purpose

This dataset aims to cover core interactions a voice assistant should manage to provide responsive and adaptive behavior in real-time communication. It can be used in tasks such as:
- Intent classification
- Dialogue system training
- Feedback management in voice assistants
