Machine Learning Slots

Overview and example of a Machine Learning Slot

This is only available for Phone 2

Overview

Machine Learning Slots are an advanced feature available exclusively for Phone 2 in the Parloa platform. Unlike list slots that rely on pre-defined values and synonyms, Machine Learning Slots are designed to handle and make sense of poorly formatted or undefined data. They offer greater flexibility in capturing and interpreting a wider array of user inputs.

Use Case Example: Undefined Shopping List Products

Let's consider an example where a user wants to add an undefined item—strawberries—to their shopping list. The Machine Learning Slot can recognize this and process it effectively.

Hi, please can you add strawberries to my shopping list

In this example, the Machine Learning Slot would process the word "strawberries" as a product entity. It's particularly useful for capturing items that are not defined in a predetermined list.

Example Response Code

Here is an example of the kind of data a Machine Learning Slot can produce:

{
  "entity":"product",
  "start":40,
  "end":50,
  "confidence_entity":0.9971703886985779,
  "value":"strawberries",
}

This response indicates that:

• The entity recognized is "product".

• The word "strawberries" starts at the 40th and ends at the 50th character in the user's sentence.

• The confidence level for recognizing this entity is approximately 99.7%.

• The value captured is "strawberries".

Future Developments

Parloa plans to launch a new service for validating if recognized items, like "strawberries," are among your offerings, adding an extra layer of functionality.

Current Best Practices

Despite the potential of ML Slots, the current best practice in Parloa is using Regular Expressions (RegEx) for accuracy and functionality. This approach ensures immediate, reliable results while we prepare for future enhancements.