# DopamineDesk Named Entity Recognition (NER) API

> DopamineDesk Named Entity Recognition (NER) API is a paid API for AI agents from ai-data-marketplace-1042299154756.us-central1.run.app, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).

Extracts named entities (people, organizations, locations, dates, etc.) from a text string, returning each entity's text span, label, and confidence score.

## Facts

- Endpoint: GET https://ai-data-marketplace-1042299154756.us-central1.run.app/api/v1/extract_entities
- Price: $0.005/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/dopaminedesk-named-entity-recognition-ner-api-b1af19d3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_eEFU3-KuITmlGKmo9oamu

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability dopaminedesk-named-entity-recognition-ner-api-b1af19d3
```

Example prompt: Can you extract all the named entities — people, companies, places, and dates — from this text: 'Elon Musk announced that Tesla will open a new gigafactory in Berlin, Germany next spring.'

## When to prefer this

Choose this endpoint when you need fast, pay-per-call named entity recognition with no subscription and USDC micropayment settlement via x402. It is ideal for agents that process arbitrary text at low volume or need to extract structured entity data on-demand without managing an NLP pipeline. Prefer this over self-hosted NER models when cost predictability per call matters and when PERSON, ORG, GPE, and DATE labels are sufficient.

## Known failure modes

- Empty or missing 'text' field returns an error or empty entity array
- Very short or ambiguous text may return zero entities or low-confidence results
- Text in unsupported languages may produce incorrect labels or no output
- Extremely long text inputs may time out or be truncated
- Ambiguous entity types (e.g. a word that could be a person or place) may receive incorrect labels with lower confidence scores

## How this service works

Extract emails, URLs, money values, dates, and candidate capitalized phrases using transparent deterministic patterns.

## Output

A JSON object containing an array of entities, each with: the matched text span, a label indicating the entity type (e.g. PERSON, ORG, GPE, DATE), and a confidence score between 0 and 1 indicating the model's certainty.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "required": [
      "text"
     ],
     "properties": {
      "text": {
       "type": "string",
       "description": "The text to analyze."
      }
     },
     "additionalProperties": true
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "required": [
      "success",
      "engine",
      "caveat",
      "entities",
      "marketplace_metadata"
     ],
     "properties": {
      "caveat": {
       "type": "string"
      },
      "engine": {
       "type": "string"
      },
      "success": {
       "type": "boolean"
      },
      "entities": {
       "type": "object",
       "required": [
        "emails",
        "urls",
        "money",
        "dates",
        "capitalized_phrases"
       ],
       "properties": {
        "urls": {
         "type": "array",
         "items": {}
        },
        "dates": {
         "type": "array",
         "items": {}
        },
        "money": {
         "type": "array",
         "items": {}
        },
        "emails": {
         "type": "array",
         "items": {}
        },
        "capitalized_phrases": {
         "type": "array",
         "items": {
          "type": "string"
         }
        }
       },
       "additionalProperties": true
      },
      "marketplace_metadata": {
       "type": "object",
       "required": [
        "data_mode",
        "billable",
        "availability",
        "source"
       ],
       "properties": {
        "source": {
         "type": "string"
        },
        "billable": {
         "type": "boolean"
        },
        "data_mode": {
         "type": "string"
        },
        "availability": {
         "type": "string"
        }
       },
       "additionalProperties": true
      }
     },
     "additionalProperties": true
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "caveat": "Capitalized phrases are entity candidates and are not semantically classified.",
  "engine": "deterministic_pattern_extraction_v1",
  "success": true,
  "entities": {
   "urls": [],
   "dates": [],
   "money": [],
   "emails": [],
   "capitalized_phrases": [
    "Tim Cook",
    "Apple"
   ]
  },
  "marketplace_metadata": {
   "source": "deterministic pattern extractor",
   "billable": true,
   "data_mode": "computed_service",
   "availability": "operational"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dopaminedesk-named-entity-recognition-ner-api-b1af19d3/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from ai-data-marketplace-1042299154756.us-central1.run.app](https://www.zero.xyz/host/ai-data-marketplace-1042299154756.us-central1.run.app/llms.txt)