ML-Assisted Labeling

ML-assisted labeling extension lets you use open-source models, LLMs, or your own models to generate labels automatically.

Overview

ML-assisted labeling helps automate data labeling for NLP projects. It supports open-source models, large language models (LLMs), and custom models for both span-based and row-based labeling tasks.

The extension generates labels automatically, helping reduce manual effort and allowing users to focus on reviewing results.

Use cases

Sentiment analysis

Use ML-assisted labeling to classify sentiment in reviews or other text data.

1. Create a row labeling project.

2. Click the gear icon from the extension panel on the right to open the Manage extensions dialog, and enable the ML-assisted labeling extension.

   
3. Select Sentiment Analysis as the service provider.

   
4. Configure Target text and Target question.

5. Click Predict labels.

6. Review the predicted labels and click Accept or Reject.

   

Span labeling with spaCy

Use the spaCy provider to automatically label entities in text.

1. Create a span labeling project.

   
2. Click the gear icon from the extension panel on the right to open the Manage extensions dialog, and enable the ML-assisted labeling extension.

   
3. Select spaCy as the service provider.

   
4. Click Predict labels.

5. Review the predicted labels and click Accept or Reject.

   

For more information about other providers, see Assisted Labeling - ML-Assisted Labeling.