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- Getting started
- Balance
- Clusters
- Concept drift
- Coverage
- Datasets
- General fields (previously entities)
- Labels (predictions, confidence levels, hierarchy, etc.)
- Models
- Streams
- Model Rating
- Projects
- Precision
- Recall
- Reviewed and unreviewed messages
- Sources
- Taxonomies
- Training
- True and false positive and negative predictions
- Validation
- Messages
- Administration
- Manage sources and datasets
- Understanding the data structure and permissions
- Create a data source in the GUI
- Uploading a CSV file into a source
- Create a new dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amend a dataset's settings
- Delete messages via the UI
- Delete a dataset
- Delete a source
- Export a dataset
- Using Exchange Integrations
- Preparing data for .CSV upload
- Model training and maintenance
- Understanding labels, general fields and metadata
- Label hierarchy and best practice
- Defining your taxonomy objectives
- Analytics vs. automation use cases
- Turning your objectives into labels
- Building your taxonomy structure
- Taxonomy design best practice
- Importing your taxonomy
- Overview of the model training process
- Generative Annotation (NEW)
- Understanding the status of your dataset
- Model training and annotating best practice
- Training with label sentiment analysis enabled
- Train
- Introduction to Refine
- Precision and recall explained
- Precision and recall
- How does Validation work?
- Understanding and improving model performance
- Why might a label have low average precision?
- Training using Check label and Missed label
- Training using Teach label (Refine)
- Training using Search (Refine)
- Understanding and increasing coverage
- Improving Balance and using Rebalance
- When to stop training your model
- Using general fields
- Generative extraction
- Using analytics and monitoring
- Automations and Communications Mining
- Licensing information
- FAQs and more
Enabling Generative Extraction
Communications Mining User Guide
Last updated Nov 7, 2024
Enabling Generative Extraction
Note:
- You need Review and Label permissions to configure and validate any extractions.
- If you defined any extraction fields on any of your labels, you automatically have Generative Extraction (GenEx) enabled.
- If you have previously annotated general fields while GenEx was not enabled, you need to provide new annotations for extraction fields, so the model can recognize the relationship between your fields and labels.
- Avoid switching back and forth between the CommPath LLM and the Preview LLM, as it can complicate tracking and managing the LLM version used for training each model. Find more information on the LLMs in the sections that follow.
To enable Generative Extraction, follow these steps:
- Configure at least one extraction field.
- Select your LLM (CommPath LLM or Preview LLM).
Note:
Regional Availability
Generative Extraction is currently only available in the US, EU, and Japan.
To find out if you can request GenEx in your region, reach out to your UiPath® Representative.