# Wikidata Entity API (`automly/wikidata-entity-api`) Actor Search Wikidata entities and export structured entity records with labels, descriptions, aliases, sitelinks, and search-match context. - **URL**: https://apify.com/automly/wikidata-entity-api.md - **Developed by:** [Automly](https://apify.com/automly) (community) - **Categories:** Developer tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Wikidata Entity API Wikidata Entity API helps you search Wikidata and export structured entity records with labels, descriptions, aliases, sitelinks, and search-match context. Use it for research, enrichment, knowledge graph lookups, and content workflows. ### Why use this actor? This actor turns Wikidata into a clean dataset you can use in AI workflows, research pipelines, and knowledge enrichment tasks. It is especially useful when you need canonical entity IDs, readable descriptions, and quick context about a person, company, product, or topic. ### Features - Search Wikidata by keyword and language - Hydrate one or more Wikidata entity IDs - Include alias summaries for richer entity context - Optionally include sitelink counts and the English Wikipedia URL - No API key required - Pay-per-event pricing aligned to successful entity records only ### Input #### Search for entities ```json { "mode": "search", "query": "OpenAI", "maxResults": 20, "language": "en" } ```` #### Hydrate entity IDs ```json { "mode": "entity", "entityIds": "Q95,Q76,Q42", "includeAliases": true, "includeSitelinks": true } ``` #### Input fields - `mode` (string): `search`, `entity`, or `both`. - `query` (string): search query used when `mode` includes search. - `entityIds` (string): comma-separated Wikidata IDs such as `Q42,Q76`. - `language` (string): language code used for search. - `maxResults` (integer): maximum records to return, capped at 50. - `includeAliases` (boolean): include a compact alias sample when hydrating entities. - `includeSitelinks` (boolean): include sitelink counts and English Wikipedia URL when available. ### Output Sample record: ```json { "recordType": "search-result", "query": "OpenAI", "entityId": "Q21708200", "title": "OpenAI", "label": "OpenAI", "description": "American artificial intelligence research organization", "conceptUri": "http://www.wikidata.org/entity/Q21708200", "wikidataUrl": "https://www.wikidata.org/wiki/Q21708200", "pageId": 23747017, "repository": "wikidata", "matchType": "label", "matchLanguage": "en", "matchText": "OpenAI", "entityType": "", "aliasesCount": 0, "aliasSample": "", "sitelinksCount": 0, "englishWikipediaUrl": "", "claimsCount": 0, "language": "en" } ``` ### Use cases - Build knowledge graphs and enrichment workflows - Normalize company, person, and topic references - Pull canonical identifiers for AI and search pipelines - Map aliases and related names into downstream systems - Improve entity resolution in content and research tools ### Limits and caveats - Search results are relevance-based, so very broad queries may require tighter wording. - Entity hydration is most useful when you provide Wikidata IDs. - Some records may have sparse English labels or descriptions. ### Pricing This actor uses pay-per-event pricing: | Event | Price | When it's charged | |-------|-------|-------------------| | `entity-record-produced` | $0.0008 / item | Per search result or entity record successfully produced | You pay only for records returned by the actor. ### FAQ #### Do I need an API key? No. Wikidata is public. #### Can I search in another language? Yes. Set `language` to the desired language code. #### What if my run charge limit is reached? The actor stops gracefully after the last chargeable record and keeps already produced items. # Actor input Schema ## `mode` (type: `string`): Choose whether to search for entities, hydrate entity IDs, or do both in one run. ## `query` (type: `string`): Wikidata search query for search mode. Example: OpenAI, climate change, Tesla. ## `entityIds` (type: `string`): Comma-separated Wikidata entity IDs for entity mode, e.g. Q42,Q76,Q95. ## `language` (type: `string`): Language for search labels and descriptions. Common values: en, ja, de, fr, es. ## `maxResults` (type: `integer`): Maximum records to return. Values above 50 are clamped for reliable runs. ## `includeAliases` (type: `boolean`): Include a compact alias summary when entity details are fetched. ## `includeSitelinks` (type: `boolean`): Include sitelink counts and the English Wikipedia URL when available. ## Actor input object example ```json { "mode": "search", "query": "OpenAI", "entityIds": "", "language": "en", "maxResults": 50, "includeAliases": true, "includeSitelinks": false } ``` # Actor output Schema ## `records` (type: `string`): All records produced by this run. ## `overview` (type: `string`): Dataset presented using the dataset schema overview view. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("automly/wikidata-entity-api").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("automly/wikidata-entity-api").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call automly/wikidata-entity-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automly/wikidata-entity-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wikidata Entity API", "description": "Search Wikidata entities and export structured entity records with labels, descriptions, aliases, sitelinks, and search-match context.", "version": "1.0", "x-build-id": "SUjuC6C9KPGeThCaG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automly~wikidata-entity-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automly-wikidata-entity-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automly~wikidata-entity-api/runs": { "post": { "operationId": "runs-sync-automly-wikidata-entity-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automly~wikidata-entity-api/run-sync": { "post": { "operationId": "run-sync-automly-wikidata-entity-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Mode", "enum": [ "search", "entity", "both" ], "type": "string", "description": "Choose whether to search for entities, hydrate entity IDs, or do both in one run.", "default": "search" }, "query": { "title": "Search query", "type": "string", "description": "Wikidata search query for search mode. Example: OpenAI, climate change, Tesla.", "default": "OpenAI" }, "entityIds": { "title": "Entity IDs", "type": "string", "description": "Comma-separated Wikidata entity IDs for entity mode, e.g. Q42,Q76,Q95.", "default": "" }, "language": { "title": "Language", "type": "string", "description": "Language for search labels and descriptions. Common values: en, ja, de, fr, es.", "default": "en" }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum records to return. Values above 50 are clamped for reliable runs.", "default": 50 }, "includeAliases": { "title": "Include aliases", "type": "boolean", "description": "Include a compact alias summary when entity details are fetched.", "default": true }, "includeSitelinks": { "title": "Include sitelinks", "type": "boolean", "description": "Include sitelink counts and the English Wikipedia URL when available.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```