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
Azure Storage Connector
Confluence Cloud Connector
Confluence Server Connector
Custom Connector
DotCMS Connector
Dropbox Connector
Google Drive Connector
Oracle Knowledge Connector
Salesforce Connector
ServiceNow Connector
SharePoint Connector
Zendesk 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
Smart Hibernation

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 stage can be used to extract entities like date, location, company name, etc from the documents. Entity extraction helps recognize specific entities within unstructured text and when an entity is identified, it enables you to take different actions based on the entity type.

Entity Extraction Configuration

Add a new stage of type Entity Extraction and configure the following properties for this stage.

  • Stage Name – Name with which this stage would be referred to. 
  • Condition – The condition which defines the documents or records on which the entity extraction definition will be performed. The condition can be defined in two ways: basic and script. In the basic method, you can perform some basic checks on one or more index fields. If the conditions are satisfied, the entity extraction rules defined are applied on the documents. In case of script method, use a custom script to identify the records for entity extraction. 
  • Stage Definition – The definition of the source and target of the entities. You can add one or more rules to find the entities. The entity extraction will be performed in the order in which the rules are defined. 
Source Field The field from which entities are to be extracted.
Add Entities Entities to be identified from the source field. You can select one or more entities from the supported list of entities. 
Target Field Field to be used to store the extracted entities.  

 

Entity Extraction

Entity extraction stage can be used to extract entities like date, location, company name, etc from the documents. Entity extraction helps recognize specific entities within unstructured text and when an entity is identified, it enables you to take different actions based on the entity type.

Entity Extraction Configuration

Add a new stage of type Entity Extraction and configure the following properties for this stage.

  • Stage Name – Name with which this stage would be referred to. 
  • Condition – The condition which defines the documents or records on which the entity extraction definition will be performed. The condition can be defined in two ways: basic and script. In the basic method, you can perform some basic checks on one or more index fields. If the conditions are satisfied, the entity extraction rules defined are applied on the documents. In case of script method, use a custom script to identify the records for entity extraction. 
  • Stage Definition – The definition of the source and target of the entities. You can add one or more rules to find the entities. The entity extraction will be performed in the order in which the rules are defined. 
Source Field The field from which entities are to be extracted.
Add Entities Entities to be identified from the source field. You can select one or more entities from the supported list of entities. 
Target Field Field to be used to store the extracted entities.