Ner

Last 30 days

Uptime

100%

Response time

273 ms typical, 424 ms slowest 5%

Last check

14 min ago

Next check

in 15 min

How to call it

# See the payment challenge (nothing is charged)
curl -i -X POST "https://tanod.dev/v1/ner" \
  -H "content-type: application/json" \
  -d '{"text":"Apple paid $3.5 million to John Smith in Berlin on 5 October 2026."}'

import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { ExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

const client = new x402Client().register(
  "eip155:8453",
  new ExactEvmScheme(privateKeyToAccount(process.env.AGENT_KEY)),
);
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? Preflight it first for $0.005:
// GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Ftanod.dev%2Fv1%2Fner
const res = await pay("https://tanod.dev/v1/ner", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({"text":"Apple paid $3.5 million to John Smith in Berlin on 5 October 2026."}),
});
console.log(await res.json());

Example input

{
  "text": "Apple paid $3.5 million to John Smith in Berlin on 5 October 2026."
}

Example output

{
  "chars_analyzed": 66,
  "chunks": 1,
  "counts": {
    "DATE": 1,
    "GPE": 1,
    "MONEY": 1,
    "ORG": 1,
    "PERSON": 1
  },
  "entities": [
    {
      "end": 5,
      "label": "ORG",
      "start": 0,
      "text": "Apple"
    },
    {
      "end": 23,
      "label": "MONEY",
      "start": 11,
      "text": "$3.5 million"
    },
    {
      "end": 37,
      "label": "PERSON",
      "start": 27,
      "text": "John Smith"
    },
    {
      "end": 47,
      "label": "GPE",
      "start": 41,
      "text": "Berlin"
    },
    {
      "end": 65,
      "label": "DATE",
      "start": 51,
      "text": "5 October 2026"
    }
  ],
  "entities_truncated": false,
  "model": {
    "id": "en_core_web_sm-3.8.0",
    "license": "MIT",
    "revision": "3.8.0",
    "source": "explosion/spacy-models (en_core_web_sm)"
  },
  "note": "offsets are Python string indices (Unicode code points), end exclusive; English model (OntoNotes labels)"
}

Security scan

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