GETTING STARTED
SearchAssist Overview
SearchAssist Introduction
Onboarding SearchAssist
Build your first App
Glossary
Release Notes
What's new in SearchAssist
Previous Versions

CONCEPTS
Managing Sources
Introduction
Files
Web Pages
FAQs
Structured Data 
Connectors
Introduction to Connectors
SharePoint Connector
Confluence Cloud Connector
Confluence Server Connector
Zendesk Connector
ServiceNow Connector
Salesforce Connector
Azure Storage Connector
Google Drive Connector
Dropbox Connector
Oracle Knowledge Connector
DotCMS Connector
RACL
Virtual Assistants
Managing Indices
Introduction
Index Fields
Traits
Workbench
Introduction to Workbench
Field Mapping
Entity Extraction
Traits Extraction
Keyword Extraction
Exclude Document
Semantic Meaning
Snippet Extraction
Custom LLM Prompts
Index Settings
Index Languages
Managing Chunks
Chunk Browser
Managing Relevance
Introduction
Weights
Highlighting
Presentable
Synonyms
Stop Words
Search Relevance
Spell Correction
Prefix Search
Custom Configurations
Personalizing Results
Introduction
Answer Snippets
Introduction
Extractive Model
Generative Model
Enabling Both Models
Simulation and Testing
Debugging
Best Practices and Points to Remember
Troubleshooting Answers
Answer Snippets Support Across Content Sources
Result Ranking
Facets
Business Rules
Introduction
Contextual Rules
NLP Rules
Engagement
Small Talk
Bot Actions
Designing Search Experience
Introduction
Search Interface
Result Templates
Testing
Preview and Test
Debug Tool
Running Experiments
Introduction
Experiments
Analyzing Search Performance
Overview
Dashboard
User Engagement
Search Insights
Result Insights
Answer Insights

ADMINISTRATION
General Settings
Credentials
Channels
Team
Collaboration
Integrations
OpenAI Integration
Azure OpenAI Integration
Custom Integration
Billing and Usage
Plan Details
Usage Logs
Order and Invoices

SearchAssist APIs
API Introduction
API List

SearchAssist SDK

HOW TOs
Use Custom Fields to Filter Search Results and Answers
Add Custom Metadata to Ingested Content
Write Painless Scripts
Configure Business Rules for Generative Answers

Entity Extraction

Entity Extraction extracts the required information from user input to accomplish the task. SearchAssist application uses NLP techniques to find named entities from the source field. 

The Entity Extraction stage in Index Pipeline can be used to identify a set of entities from a source field and save the identified entities in a target field so that it can be used to identify the intention of the search user better.

You can:

  • Add multiple entities to be extracted from the source field.
  • Define a condition for the entity extraction stage. The entities are extracted only from the documents that satisfy the given condition.
  • Re-order or delete entity extraction rules.
  • Simulate the changes before saving them.

Ensure to Train your app each time you make changes to any index configuration. This builds the index based on the updated configurations.

Configuration

To configure entity extraction, follow the below steps:

  1. Click the Indices tab on the top.
  2. On the left pane, under the Index Configuration section, click Workbench.
  3. On the Workbench (Index Configuration) page, on the Stages column, click the + icon.
  4. On the right column, select Entity Extraction from the Stage Type drop-down list.
  5. Enter a name in the Stage Name field.
  6. Enter a condition in the Condition field. You can add multiple conditions using the AND/OR connectors. Documents that satisfy the condition will be executed as part of the stage. See below for details.
  7. Select the field you want to extract entity from as Source Field.
  8. Define where you want to store the extracted entity as Target Field. This field is created by the application.
  9. Select an entity from the Add Entities field. These are the entity types that need to be identified from the source field. The supported entities are Date, Time, Date-Time, Date Period, URL, Email, Location, City, Country, Color, Company Name, Currency, Person Name, Number, Percentage, Phone Number, Zip Code, Quantity, Address, and Airport.
  10. Click Simulate to verify the configurations. The simulator displays the Source and the number of documents to which the mapping was applied, and the result. You can change the Source (if not mentioned in the condition) and the number of documents.
  11. Once done, click Save Configuration on the top-right.

Conditions

Condition is of the following format: ctx.fieldtype==value or ctx.fieldtype!=value. The field_name can be obtained from the Fields table under Index Configuration.

For example, ctx.contentType=="web" to restrict the extraction to the content from a web source.

Entity Extraction

Entity Extraction extracts the required information from user input to accomplish the task. SearchAssist application uses NLP techniques to find named entities from the source field. 

The Entity Extraction stage in Index Pipeline can be used to identify a set of entities from a source field and save the identified entities in a target field so that it can be used to identify the intention of the search user better.

You can:

  • Add multiple entities to be extracted from the source field.
  • Define a condition for the entity extraction stage. The entities are extracted only from the documents that satisfy the given condition.
  • Re-order or delete entity extraction rules.
  • Simulate the changes before saving them.

Ensure to Train your app each time you make changes to any index configuration. This builds the index based on the updated configurations.

Configuration

To configure entity extraction, follow the below steps:

  1. Click the Indices tab on the top.
  2. On the left pane, under the Index Configuration section, click Workbench.
  3. On the Workbench (Index Configuration) page, on the Stages column, click the + icon.
  4. On the right column, select Entity Extraction from the Stage Type drop-down list.
  5. Enter a name in the Stage Name field.
  6. Enter a condition in the Condition field. You can add multiple conditions using the AND/OR connectors. Documents that satisfy the condition will be executed as part of the stage. See below for details.
  7. Select the field you want to extract entity from as Source Field.
  8. Define where you want to store the extracted entity as Target Field. This field is created by the application.
  9. Select an entity from the Add Entities field. These are the entity types that need to be identified from the source field. The supported entities are Date, Time, Date-Time, Date Period, URL, Email, Location, City, Country, Color, Company Name, Currency, Person Name, Number, Percentage, Phone Number, Zip Code, Quantity, Address, and Airport.
  10. Click Simulate to verify the configurations. The simulator displays the Source and the number of documents to which the mapping was applied, and the result. You can change the Source (if not mentioned in the condition) and the number of documents.
  11. Once done, click Save Configuration on the top-right.

Conditions

Condition is of the following format: ctx.fieldtype==value or ctx.fieldtype!=value. The field_name can be obtained from the Fields table under Index Configuration.

For example, ctx.contentType=="web" to restrict the extraction to the content from a web source.