Entity Recognition
POST
https://vulavula-services.lelapa.ai/api/v1/entity_recognition/process.
The Named Entity Recognition (NER) endpoint analyses the provided text and identifies named entities such as persons, locations, and more. Each request can handle up to 2,000 tokens, with 180 tokens recommended for optimal performance.
BODY PARAMS
encoded_text string required.
This parameter represents the text input that will be analysed for named entities. It is required for the endpoint to function properly. The encoded_text
should be provided as a string and contains the text to be processed by the Named Entity Recognition (NER) model. The text may include any language and should ideally be encoded in a format suitable for NER processing, ensuring accurate entity detection.
HEADERS
X-CLIENT-TOKEN string required.
Represents the authentication token required for accessing the API. This header ensures that only authorized clients can make requests to the endpoint.
EXAMPLES
pdm add vulavulabash
from vulavula import VulavulaClient client = VulavulaClient("<INSERT_TOKEN>") entity_result = client.get_entities({'encoded_text': 'President Ramaphosa gaan loop by Emfuleni Municipality.'}) print("Entity Recognition Output:", entity_result)python
RESPONSES
🟢 200 OK
[ { "entity": "person", "word": "Ramaphosa", "start": 10, "end": 19 }, { "entity": "location", "word": "Emfuleni Municipality", "start": 33, "end": 54 } ]json
RESPONSE BODY PARAMS
Object |
---|
entity string required. Specifies the type of the recognized entity (e.g., person, location). |
word string required. Contains the text representing the recognized entity. |
start number required. Indicates the starting index of the recognized entity in the input text. |
end number required. Indicates the ending index of the recognized entity in the input text. |