Entity Extraction
Extracts entities like names, locations or numbers from any texts.
Overview
Entity Extraction is a powerful tool that allows you to automatically identify and extract named entities from text.
This AI block uses advanced natural language processing techniques to analyze the input and identify entities such as people, organizations, locations, and dates. It can also identify other types of entities, such as products, events, and concepts.
Entity Extraction is useful for a wide range of applications, including information retrieval, content analysis, and data mining.
It can help you to quickly and accurately identify key information in large volumes of text, making it easier to analyze and understand.
You can adjust the confidence threshold, filter the types of entities to extract, and customize the output format after it.
How to Setup
Provide text input to extract entities from.
Set the name of the output data variable (optional)
Change the confidence score (optional) - the higher it is, the fewer entities you have in the output, and vice versa.
All the entities are in the same text variable, separated by commas.
If you need to split them into multiple entries for further processing in the workflow (i.e. searching for additional info on all of them using Google) - use Split block after it.
Inputs and Outputs
| Input | Output | Output Description |
|---|---|---|
Any Text (x1 text) | Entities (x1 text) | Extract named entities, like personal names, company names, numbers, or locations with their entity types. |
Last updated
