Efficient Data Annotation With Annolive’s Bulk Annotation

Welcome to this guide to bulk annotate your whole data with a single click in Annolive, using GPT or your own trained model. In the fast paced AI world, it is important to get the data ready quickly. Bulk Annotation feature in Annolive lets you to label the data using LLM/pretrained models in a single click. Users can further refine the bulk annotated result for better accuracy. This in turn reduce the effort on the annotation task by 80%

Bulk Annotation workflow

What are we going to do:

  1. Select the Task in the project
  2. Configure the models for auto-annotation
  3. Bulk Annotate and refine the data

Bulk Annotation

Bulk annotation is the process of annotating all the data with a single click. Users can define the model to be used for this annotation. Once the data is annotated, users can refine the data to ensure the data quality

Annolive supports the use of both publicly available models and your own proprietary models for bulk annotation. If you are using LLMs, annolive lets you to tune the prompt before annotating the whole data

1. Select the Task in the project

In Annolive, a ‘task’ means an annotation task/job. Select the project form projects page. Navigate to the tasks tab in the side bar. Click on the task for annotation

More details on creating the task in Annolive can be found here

2. Configure the models for auto-annotation

Go to the task page

  1. Navigate to the Settings tab within the task view.
  2. In the Settings tab, Activate auto annotation by toggling the enable button.
  3. Choose the required pre-trained model. If you have a custom model, select custom model from the dropdown menu.
  4. If you’ve chosen a custom model, provide the HTTP link to the custom model interface.
Annolive GLiNER integration

3. Bulk Annotate and Refine the Data

Proceed to the Bulk Annotate options in Settings and click the Start button.

Once the bulk annotation process is completed, you can go to individual data items, if necessary, to refine the annotations. Or you can directly export the annotated dataset

References

FAQs

What is bulk annotation?
Bulk annotation is a process that allows you to label an entire dataset with a single click, using pre-trained models or proprietary models. It significantly reduces the manual effort required for data annotation.
Can I use my own models for bulk annotation in Annolive?
Yes, Annolive supports the use of custom proprietary models in addition to publicly available pre-trained models. Users can provide an HTTP link to their custom model interface.
What are the benefits of using bulk annotation?
Bulk annotation accelerates the data labeling process, enhances consistency, and reduces manual effort. It is particularly effective for large datasets.
What are the steps involved in using bulk annotation in Annolive?
Select the annotation task from the project. Configure the auto-annotation settings by enabling the feature and selecting a model. Start bulk-annotation and refine the annotated data if needed
Does Annolive provide support for prompt tuning?
Yes, when using large language models (LLMs) for bulk annotation, Annolive allows you to fine-tune prompts to achieve better annotation results.
How does Annolive’s bulk annotation feature work?
Annolive enables users to select a task, configure models for auto-annotation, and annotate data in bulk. The results can then be refined for better accuracy, reducing annotation efforts by up to 80%.
What types of models can be used for auto-annotation in Annolive?
Annolive supports both large language models (LLMs) like GPT and custom-trained models. You can also tune prompts for LLMs to optimize annotation results.
Can I edit annotations after the bulk annotation process?
Yes, once the bulk annotation is complete, you can refine individual data items to ensure quality and accuracy before exporting the annotated dataset.
How do I configure a custom model for auto-annotation?
Navigate to the Settings tab of the task, enable auto-annotation, and select “Custom Model” from the dropdown. Provide the HTTP link for the model interface to complete the configuration.
Where can I find additional resources or support for Annolive?
You can access detailed documentation on tasks and bulk annotation here, or reach out via Contact Us.

Thanks for reading. Please contact us for any queries.

Last Updated on 19/11/2024