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Getting Started

Explore

User permissions required: ‘View Sources’ AND ‘View Labels’

  

Overview

  

The Explore page allows you to search, review and filter a dataset to inspect and review individual verbatims. 

 

 

Explore page

 

By default, Explore presents the 20 most recent verbatims in a dataset, you can click the query button in the top right-hand corner of the page to change this.

 

 

Query button


The different options you can select from the dropdown menu are:

 

  • Recent – view 20 most recent verbatims
  • Shuffle – view 20 random verbatims
  • Teach – show 20 verbatims that Re:infer is unsure how to label
  • Low confidence – show 20 verbatims for which Re:infer currently has very low confidence about which labels may apply


If you have a label selected from the label filter bar (explained below), the dropdown will contain a few more options:

 

  • Labelview 20 verbatims with the selected label assigned / predicted (this is the default mode when a label is selected)
  • Check label - view 20 verbatims that may have the selected label applied incorrectly
  • Missed label - view 20 verbatims that may be missing the select label


At the bottom of the page you can click to move to the next page of 20 verbatims, or go back to a previous page.

  

To understand more about how to use Explore, see here.


Filter bar & adding or removing filters


The filter bar on the left-hand side of the page (as shown below) allows you to find specific groups of verbatims.


From this filter bar you can filter to:

  • Specific date ranges (pick exact dates or select from options like the last week, month, 90 days or year)
  • Reviewed or unreviewed verbatims
  • Verbatims with positive or negative sentiment predictions (if sentiment is enabled on the dataset)
  • Add any filter based on the metadata properties associated with your verbatims (click 'Add a new filter')

  

 

Filter bar

 

When you add a filter to metadata fields with a string format, you will be able to choose which to include or exclude in your selection (as shown in the two examples below):

 

 

 

Example inclusion and exclusion filters for a string format metadata fields

 

Please Note: When you choose to include certain values for a user property, you automatically exclude the remainder (and vice versa).

 

If you add a filter to metadata fields with a number format, you will be able to select minimum or maximum values (as shown below), to create a range of your choice:

 

 

Filter for number format metadata fields


To remove a filter that you've applied, simply click the bin icon that appears when you hover over it with your mouse (as shown below), or select 'Clear All' at the top of the filter bar, to remove all filters applied.

 

  

Filter showing the 'remove filter' icon


Label bar


You can also use Explore to view verbatims with specific labels, to do so click the label name in the label bar below the filter bar. 

 

You can use the buttons at the top of the label bar to filter between showing all verbatims, to those that have had labels assigned to them, or those with predictions (that have not been reviewed).


To update the filter from showing all verbatims to either those with assigned labels or predicted labels, use the buttons explained below. They change colour when selected:

Select verbatims that have assigned labels
Select verbatims that have labels predicted

To deselect the filter, simply click the button again.


If you select neither button, but filter to a label, the platform will show you all verbatims that either have the label pinned or predicted, started with the reviewed verbatims first.


 

Label bar guide

 

  • The training health circle (see here for explanation) next to some labels highlights those which require more training examples for Re:infer to accurately evaluate the performance of the label
  • The completeness of the circle indicates how many more examples are needed. The larger the red section, the more examples are required
  • Once you have 25 labelled examples, the red circle will disappear (depending on the complexity of the label, however, you may still need more examples to get accurate predictions)
  • You should review verbatims to find more training examples

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