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Explore

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


What's covered in this article:


 

Overview

  

The Explore page allows you to search, review and filter a dataset to inspect and review individual verbatims and entities. You can navigate the the Explore page by clicking 'Explore' on the top navigation bar.  

 

 

Explore page

 

By default, Explore presents the 20 most recent verbatims in a dataset in the 'Recent' mode, you can click the dropdown mode selector in the top left-hand corner of the page to change this.

 

 

Dropdown mode selector


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 the platform is unsure how to label
  • Low confidence – show 20 verbatims which are not well covered by informative label predictions
  • Rebalance - show 20 verbatims that are underrepresented by the training data in your dataset 
  • Label - view 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 and 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 to verbatims that have specific entities predicted or assigned
  • Filter to verbatims that have (or do not have) a specific label or combination of labels predicted (see the article on Advanced Prediction Filters for more detail)

  

 

Filter bar


 

 

Adding a user property filter

 

When you click 'Add a new filter', the dropdown shows a full list of all the available property filters.


These are naturally grouped by categories, and some are unique to the communication type in the dataset, e.g. email.


The property categories that properties are grouped together in are:

  

  • Source - this only appears if there is more than one source in the dataset
  • Email - these are specific to individual emails, e.g. who sent it
  • Thread - these are email specific and relate to the characteristics of email threads
  • User - all other metadata properties uploaded (and not derived by the platform) with each verbatim

 


Filter dropdown showing different property categories

 

To the left of each property, an icon indicates the property type, whether it's a number or string. For string user properties, the platform provides an example value on hover (see below).


 

Filter dropdown showing example property value

 

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 filters for a string format metadata field

 

Example exclusion filters for a string format metadata field

 

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

 

 

Removing a property filter


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 filter


Please Note: The introduction of Advanced Prediction Filters means that the label filter bar no longer automatically selects the 'Label' training mode, nor do you use it to select a label to train whilst in another mode such as 'Check label', this is now done via the taxonomy dropdown that appears after you select a training mode from the dropdown menu shown above.


You can use the label filter bar to filter to verbatims that have (or do not have) specific labels predicted, either whilst Model Training or whilst exploring and interpreting your data. To see how they work in more detail, see the article on Advanced Prediction Filters here.  

 

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). The icons are shown below, and 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 filter to all verbatims that either have the label pinned or predicted, starting with the reviewed verbatims first.


 

Label bar guide

 

The label filter bar and '+ Add label filter' allow you to add complex combination or inclusion and exclusion filters (i.e. show me verbatims with X and Y predicted, but not Z). To find out more about how to use these, see the 'Advanced Prediction Filters' article here.


Red dial training indicator: 

 

  • The red dial training indicator (see here for explanation) next to some labels highlights those which require more training examples for the platform 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 need more examples to get accurate predictions)
  • You should review verbatims to find more training examples


Thread view (email specific data)

 

 For datasets containing emails, these are displayed showing the email that matches the selected sort order (e.g. Teach Label, Missed Label, etc.), but with easy access to the other emails that are in the same email thread.


In the example below, you can see the sorted email is in a thread of three emails, and this is the third email in the thread.

 


Normal email view for an email matching the current sort order and/or filters selected in Explore


 

By clicking the bi-directional arrow icon below the subject, you can expand out the email thread to show partial views of the other emails in the thread, as seen below:
  

 

Partially expanded thread view showing the sorted email and partials of the other emails in the thread

  

 

If you click again on any of the partially expanded emails, they will be expanded in full like the original sorted email, as seen below:

 

 

Fully expanded thread view showing all three full emails in this particular thread

 

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