v1

latestOpenAPI 3.0.32026-07-26451985.7 KB

token-classification

Identify and categorize tokens in text for Named Entity Recognition (NER), Part-of-Speech tagging, and other NLP tasks

post/models/v2/dslim/bert-base-NER

Request body

textstring required

The input text

Example request

{
  "text": "John Doe is a software engineer at Google"
}

Response

Successful token-classification response.

errorstring nullable required

Null on success; otherwise an error message.

Example response

{
  "output": [
    {
      "entity": "B-PER",
      "score": 0.9996556043624878,
      "index": 1,
      "word": "John",
      "start": 0,
      "end": 4
    },
    {
      "entity": "I-PER",
      "score": 0.999683141708374,
      "index": 2,
      "word": "Do",
      "start": 5,
      "end": 7
    },
    {
      "entity": "I-PER",
      "score": 0.9945255517959595,
      "index": 3,
      "word": "##e",
      "start": 7,
      "end": 8
    },
    {
      "entity": "B-ORG",
      "score": 0.9984006285667419,
      "index": 9,
      "word": "Google",
      "start": 35,
      "end": 41
    }
  ]
}