{"uid":"cap_iE2WW-ItGhsjkIpzOXBTu","slug":"nexusapi-named-entity-recognition-ner-248e6004","name":"NexusAPI Named Entity Recognition (NER)","description":"Crypto, AI, Social Media, Finance, Weather, Tools & more. Pay per call in USDC on Base. No API keys.","url":"https://nexus-api-virid.vercel.app/api/ai/ner","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"query":{"type":"string","description":"Search query or input parameter"}}},"responseSchema":{"type":"object","description":"API response data"},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.110144","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.110144/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.110144","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.110144","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_k_IV5rSuGa8uAZEoyWa4x","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.110144","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Performs Named Entity Recognition (NER) on a text query, identifying and classifying named entities such as people, organizations, locations, and dates.","exampleAgentPrompt":"Extract all named entities from this text and tell me what type each one is: 'Apple CEO Tim Cook met with Elon Musk in San Francisco on Tuesday to discuss AI regulation.'","exampleUseCases":[{"title":"Entity extraction from news articles","prompt":"Pull out all the named entities — people, organizations, and locations — from this news snippet: 'Amazon founder Jeff Bezos visited the White House in Washington D.C. last Monday.'"},{"title":"CRM enrichment from customer messages","prompt":"I have this customer email: 'Hi, I'm John Smith from Acme Corp in Chicago, reaching out about your enterprise plan.' Can you identify all the named entities in it so I can auto-populate our CRM fields?"},{"title":"Legal document entity tagging","prompt":"Identify and label all named entities in this legal clause: 'On March 5, 2024, Google LLC entered into an agreement with Microsoft Corporation, governed by the laws of the State of California.'"}],"resultDescription":"A structured response identifying spans of text that are named entities, along with their classified types (e.g. PERSON, ORG, LOCATION, DATE, etc.) extracted from the input text.","failureModes":["Empty or missing query field returns an error or empty entity list","Very long text inputs may be truncated or cause timeouts","Ambiguous entity types may be misclassified (e.g. a person name matching a place name)","Non-English text may return poor or no results if the model is English-only","Payment failure via x402 protocol results in 402 response and no entity data returned"],"whenToPreferThis":"Choose this endpoint when you need a pay-per-call, no-API-key NER service that accepts raw text and returns structured entity labels. Ideal for agents that need lightweight entity extraction without managing credentials or subscriptions. Use it when you need to identify people, organizations, locations, or dates in arbitrary text as part of a larger workflow.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T12:41:03.697Z","isFirstParty":false}