The entity extraction & linking operation identifies entities and relates them to entities stored in the knowledge bases. For example, "Barack Obama" and "President Obama" are mapped to "President Barack Obama," and the linker adds the "POLITICIAN" entity type. Using it, you can detect the organizations, people, and other entities in your text data.

Step-by-step guide

1. Open the operation configuration window

Click the "Add operation" button at the top of the workspace.

Search for "Extract and link entities" or find the operation under "Text enrichment" and click it.

2. Choose text input

In the "Text source" part, select the input text you want to process.

2. Choose language

In the "Language" drop-down, select the language of your input text. Currently, English is the only available language for this operation.

3. Name the output field

Under "Output field name,” type the name of the output field.

4. Apply the operation

Click "Apply" to run the operation. Then, Entities collection is generated, as it is visible in the Table View. To see the entities in detail, create a new Table View and carry the dataset from Schema to the new Table View workbench. As visible, the Entities collection is composed of 3 different fields: entity, linked_entity, and type. Entity refers to the detected item, linked_entity refers to the entity found in the knowledge base and linked. The type shows the identified entity type. This way, entities are identified and linked to provide more information about text data.

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