Quick Start Guide

Get up and running with Entity Detector in 5 minutes.

Step 1: Create an Account

Step 2: Get Your API Token

Log in to your dashboard
Navigate to the "API Tokens" section
Click "Create New Token"
Copy your token (it's only shown once!)

Important: Keep your API token secret. Don't commit it to version control or expose it in client-side code. Use environment variables instead.

Step 3: Make Your First Request

Send a POST request to the /v1/analyze endpoint with your text:

Using cURL

bash

curl -X POST https://api.entitydetector.com/v1/analyze \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "text": "Elon Musk announced that Tesla will open a new factory in Berlin, Germany. The CEO expects production to begin in 2024."
  }'

Using Node.js

javascript

const response = await fetch('https://api.entitydetector.com/v1/analyze', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_API_TOKEN'
  },
  body: JSON.stringify({
    text: 'Your article text here...'
  })
});

const data = await response.json();
console.log(data.entities);

Using Python

python

import requests

response = requests.post(
    'https://api.entitydetector.com/v1/analyze',
    headers={
        'Content-Type': 'application/json',
        'Authorization': 'Bearer YOUR_API_TOKEN'
    },
    json={
        'text': 'Your article text here...'
    }
)

data = response.json()
print(data['entities'])

Step 4: Parse the Response

The API returns a JSON object with entities, relations, and metadata:

json

{
  "entities": {
    "persons": ["Elon Musk"],
    "organizations": ["Tesla"],
    "locations": ["Berlin", "Germany"],
    "objects": ["factory"]
  },
  "relations": [
    {
      "source": "Elon Musk",
      "target": "Tesla",
      "type": "leads",
      "evidence": "The CEO",
      "sentiment": "neutral",
      "confidence": 0.95
    },
    {
      "source": "Tesla",
      "target": "Berlin",
      "type": "located_in",
      "evidence": "open a new factory in Berlin",
      "sentiment": "positive",
      "confidence": 0.92
    }
  ],
  "meta": {
    "model": "qwen2.5:1.5b-instruct",
    "language": "en",
    "processingMs": 1847,
    "cached": false
  }
}

Response Fields

entities - Named entities grouped by type (persons, organizations, locations, objects)
relations - Connections between entities with type, evidence, sentiment, and confidence
meta - Request metadata including model used, detected language, and processing time

Next Steps

API Reference

Full endpoint documentation

Code Examples

More language examples

Rate Limits

Understand usage quotas

Error Handling

Handle errors gracefully