Named Entity Recognition (NER) use case
In the Named Entity Recognition (NER) use case, the LLM ingests text and entities to extract and return a JSON response that contains a list of entities extracted from the text. No options can be configured.
This use case can be used to extract nouns and proper nouns such as Brand, Date, Company, Places, and Category in order to guide and refine searches.
The POST request obtains and indexes prediction information related to the specified use case, and returns a unique predictionId and status of the request. The predictionId can be used later in the GET request to retrieve the results.
Documentation Index
Fetch the complete documentation index at: https://doc.lucidworks.com/llms.txt
Use this file to discover all available pages before exploring further.
Headers
Bearer token used for authentication. Format: Authorization: Bearer ACCESS_TOKEN.
application/json
"application/json"
Path Parameters
Unique identifier for the model.
Body
The batch of key:value pairs used as inputs in the prediction. Up to 32 inputs per request are allowed.
32Provides fields and values that specify ranges for tokens. Fields used for specific use cases and models are specified. The default values are used if other values are not specified.
Response
OK
This is the response to the POST prediction request submitted for a specific useCase and modelId.
The universal unique identifier (UUID) returned in the POST request. This UUID is required in the GET request to retrieve results.
The current status of the prediction. Allowed values are:
-
SUBMITTED - The POST request was successful and the response has returned the
predictionIdandstatusthat is used by the GET request. -
ERROR - An error was generated when the GET request was sent.
-
READY - The results associated with the
predictionIdare available and ready to be retrieved. -
RETRIEVED - The results associated with the
predictionIdare returned successfully when the GET request was sent.
"SUBMITTED"