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OmniAPI Named Entity Recognition (NER)
x402
OmniAPI Named Entity Recognition (NER) is a paid API for AI agents from omni-api-cyan.vercel.app, paid per call via x402, $0.110144/call, status unknown (last checked 2026-09-15).
Extracts named entities (people, organizations, locations, dates, etc.) from input text using AI-powered NER
Price / call$0.110144
Success—
StatusUnknown
How this service works
444 endpoints across 9+ chains. Crypto, AI, Social, Finance, Weather, Tools. Pay per call in USDC via x402 with 4 facilitators: Dexter, Meridian, FluxA, GoPlausible.
Output
Returns a structured object containing identified named entities extracted from the input text, with each entity labeled by its type (e.g. PERSON, ORG, LOCATION, DATE) and its corresponding span or value from the original text.
Example use cases
Entity extraction from news article
“Pull out all the people, organizations, and locations mentioned in this news snippet: 'Elon Musk's SpaceX launched a rocket from Cape Canaveral on Monday, in cooperation with NASA.'”
Structured data from customer feedback
“Identify any company names, product names, and people mentioned in this customer review: 'I contacted Sarah from Acme Corp about my broken DX-500 blender and she was very helpful.'”
Document annotation for legal contract
“Find and label all named entities in this contract clause — especially organization names, person names, and dates: 'On January 15, 2024, GlobalTech Inc. and John Smith agreed to the following terms.'”
Technical details
Endpoint
POSThttps://omni-api-cyan.vercel.app/api/ai/nerWhen to prefer
Choose this endpoint when you need to identify and classify named entities (people, places, organizations, dates) from free-form text as part of a pipeline — especially when paying per-call via USDC x402 is acceptable and you need a simple POST interface without setting up your own NLP model infrastructure.
Side effects
- Missing required 'query' field returns a validation error
- Empty or very short text may yield no entities or low-confidence results
- Ambiguous proper nouns may be misclassified between entity types
- Non-English or heavily domain-specific text may reduce extraction accuracy
- Payment failure via x402 protocol returns HTTP 402 and no result
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | string | Input data for the endpoint |
| queryrequired | string | Search query or input text |
| params | object | Additional parameters |
Output
Schema · Response
{
"type": "object",
"description": "API response data"
}Tags
x402
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