User Guide
eva 3.4.1
eva 3.4.1
  • Home and Support
  • What's new
  • Changelog
  • Using eva
    • Overview
      • Virtual Agents
      • Main Concepts of eva
      • Glossary
    • Developing virtual agents
      • Quick Start with eva
      • Dialog Flows
      • Dialog Cells
        • Intent Cells
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        • End Cells
        • Code Cells
        • Rule Cells
      • Training task
      • Export and import agents
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    • Channels
      • Integrating Existing Channels
    • Testing Virtual Agents
      • Test a virtual agent
      • Automated Test
    • Natural Language
      • eva NLP
      • Training with eva NLP
      • Training with eva Automated Learning
      • Using other NLP engines
    • Analytics
      • External analytics platforms
    • Experience
      • Context Management
    • Advanced Options
      • Parameters
      • Intent Navigator
      • PII Data masking
    • How Tos
      • Creating variable answers with Code and Rule cells
      • Videos
  • for technicians
    • eva server Installation guide
    • API Guidelines
      • Conversation API
      • Cloner API
      • Webhooks
    • Supported/verified third-party software
    • Appendices
    • Data Extraction
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  2. Natural Language

Training with eva NLP

After building a flow, you have to make sure that they are connected to the right answers. Here, you will learn the best way to do this

Previouseva NLPNextTraining with eva Automated Learning

Last updated 3 years ago

If you are using NTT DATA eva NLP, you will have to train your Intents and Entities using the eva cockpit. Every time an Intent, Entity, document, or question is changed, the button “Train” will appear in the training section. Just click it.

Training a virtual agent is very easy! You'll just have to go to the training repository:

Lists of trainings

All trained versions (valid and invalid) are kept in the training repository. The latest trained version will be automatically published.

Important:

  • You can publish only one version at a time.

  • To train a flow in eva NLP, you must have at least five (5) intents with at least five (5) examples each. A virtual agent will not be trainable if it has any intents with less than five (5) examples.

  • If you delete an intent or example/utterance in the repository, the training will be invalid. Entities don’t have minimum values.

After training, you can check the details of the training.

By clicking on “Details”, you will be taken to a page with that specific training.

If something goes wrong, you can see why by clicking on “view details” after the X icon.

Training Details
Failed Training
Training button