# Entity Deduplication Matcher (`junipr/entity-deduplication-matcher`) Actor Fuzzy-match and deduplicate company, product, location, or entity rows into canonical records. - **URL**: https://apify.com/junipr/entity-deduplication-matcher.md - **Developed by:** [junipr](https://apify.com/junipr) (community) - **Categories:** SEO tools, Developer tools, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.80 / 1,000 target auditeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## Entity Deduplication Matcher ### Store Positioning **Store title:** Entity Deduplication Matcher **Short description:** Fuzzy-match and deduplicate company, product, location, or entity rows into canonical records. **SEO title:** Entity Deduplication Matcher — data QA, validation, and cleanup utility **SEO description:** Fuzzy-match and deduplicate company, product, location, or entity rows into canonical records. Use it to validate rows, schemas, duplicates, field quality, and delivery-readiness before handing data to clients or automations. **Categories:** SEO_TOOLS, DEVELOPER_TOOLS, ECOMMERCE **Keywords:** entity, deduplication, matcher, data/schema qa utility ### Fixed-Inclusive PPE Pricing This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model. - Tier: U2 — Data/schema QA utility - Primary event: `record-matched` at $0.00390 base - Default max charge: $5.00 - Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount Event set: - `actor-start`: base $0.00500, GOLD $0.00400. Entity Deduplication Matcher: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `record-matched`: base $0.00390, GOLD $0.00312. Entity Deduplication Matcher: charged when record matched is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `issue-detected`: base $0.00372, GOLD $0.00298. Entity Deduplication Matcher: charged when issue detected is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `qa-report-generated`: base $0.05000, GOLD $0.04000. Entity Deduplication Matcher: charged when qa report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended. ### Public Task Concepts - QA rows for Entity Deduplication Matcher - Validate data quality for Entity Deduplication Matcher - Generate a schema/quality report for Entity Deduplication Matcher - Audit entity issues across supplied public inputs - Extract evidence-backed entity rows for client QA Fuzzy-match and deduplicate company, product, location, or entity rows into canonical records. This Actor is a premium Apify tool for the use case described below. It is designed for controlled runs with capped inputs, transparent pricing, and evidence-backed outputs. ### What It Does Entity Deduplication Matcher turns supplied source evidence into actor-specific dataset rows for data cleanup workflows. It uses deterministic parsing, strict caps, supplied examples, and top-level fields that match the dataset schema. ### What It Does Not Do - It does not claim complete coverage for private, login-gated, or blocked pages. - It does not make live network calls unless `fetchUrls` is explicitly enabled. - It does not use unsupported AI claims or hidden enrichment. - It does not replace legal, financial, medical, or compliance review. ### Input Fields - `targets`: Source rows, snapshots, text, HTML, records, schemas, logs, or workflow details. - `fetchUrls`: Defaults to `false` so you can validate supplied snapshots first. Enable it when you want the Actor to fetch public URLs within configured limits. - `includeReport`: Writes JSON and Markdown artifacts when enabled. - `maxTargets`: Conservative cap for small, predictable runs. - `maxTextBytes`: Per-target text cap. ### Example Input ```json { "targets": [ { "sourceId": "fixture-entity-dedupe", "title": "Example entity dedupe", "records": [ { "name": "Acme Roofing Nashville LLC", "domain": "acmeroofing.example", "city": "Nashville", "phone": "(615) 555-0199" }, { "name": "ACME Roofing - Nashville", "domain": "www.acmeroofing.example", "city": "Nashville", "phone": "6155550199" }, { "name": "Brio Plumbing Austin", "domain": "brioplumbing.example", "city": "Austin", "phone": "(512) 555-0100" } ] } ], "maxTargets": 1, "includeReport": true, "fetchUrls": false } ```` ### Output Fields - `rowId` - `sourceId` - `sourceUrl` - `sourceType` - `status` - `severity` - `score` - `summary` - `recommendation` - `checkedAt` - `pricingTemplate` - `pricingEventName` - `clusterId` - `recordId` - `matchedRecordId` - `matchScore` - `matchReasons` - `canonicalRecord` - `decision` ### Example Output ```json [ { "rowId": "entity-deduplication-matcher_6f2c5e4d59dc49f6", "sourceId": "fixture-entity-dedupe", "sourceUrl": null, "sourceType": "records", "status": "ok", "severity": "low", "score": 92, "summary": "Entity Deduplication Matcher produced actor-specific supplied examples output for fixture-entity-dedupe.", "recommendation": "Review source evidence and keep the run capped until outputs match your operational needs.", "checkedAt": "2026-07-02T00:00:00.000Z", "pricingTemplate": "U2_P1", "pricingEventName": "record-matched", "clusterId": "cluster_1", "recordId": "record-1", "matchedRecordId": "record-2", "matchScore": 0.94, "matchReasons": [ "same-domain" ], "canonicalRecord": { "company": "Example entity dedupe" }, "decision": "merge" } ] ``` ### Public Task Concepts Example tasks are included for common use cases and can be published as Apify public tasks after review/approval. ### Limitations Coverage depends on the supplied records, snapshots, and fetch settings. Some public pages may block automated requests or expose inconsistent metadata. ### FAQ **Is this ready for production workflows?** Use capped test runs first, then increase limits only after the output shape and data behavior match your needs. **Does it use live Apify credits now?** Costs are controlled with input caps and max-charge handling. See the pricing section for event prices and cost controls. # Actor input Schema ## `targets` (type: `array`): Targets to process. Each target can include snapshots, HTML, CSV text, records, and optional source URL. ## `records` (type: `array`): Optional structured rows for one target. ## `csvText` (type: `string`): Optional CSV text for one target. ## `fetchUrls` (type: `boolean`): Fetch source URLs over HTTP. Default is false to avoid cloud usage and network variability. ## `maxItems` (type: `integer`): Alias for Max Targets/Maximum Records used by the Junipr actor baseline. When both are provided, actor-specific limits still apply. ## `includeReport` (type: `boolean`): Write JSON summary, JSON results, and Markdown report artifacts to the key-value store. ## `maxTargets` (type: `integer`): Maximum entity batch targets to process. ## `maxTextBytes` (type: `integer`): Maximum text bytes to analyze per target. ## `dryRun` (type: `boolean`): Validate input and write a dry-run summary without PPE charges or dataset output. ## `debug` (type: `boolean`): Enable debug logs. ## Actor input object example ```json { "targets": [], "records": [], "csvText": "", "fetchUrls": false, "maxItems": 1, "includeReport": true, "maxTargets": 1, "maxTextBytes": 500000, "dryRun": false, "debug": false } ``` # Actor output Schema ## `results` (type: `string`): Structured entity batch rows. ## `summary` (type: `string`): Run summary JSON when includeReport is enabled. ## `markdownReport` (type: `string`): Markdown report when includeReport is enabled. # 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("junipr/entity-deduplication-matcher").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("junipr/entity-deduplication-matcher").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 junipr/entity-deduplication-matcher --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=junipr/entity-deduplication-matcher", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Entity Deduplication Matcher", "description": "Fuzzy-match and deduplicate company, product, location, or entity rows into canonical records.", "version": "1.0", "x-build-id": "2ueFfZlbOFfbvv87I" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/junipr~entity-deduplication-matcher/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-junipr-entity-deduplication-matcher", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/junipr~entity-deduplication-matcher/runs": { "post": { "operationId": "runs-sync-junipr-entity-deduplication-matcher", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/junipr~entity-deduplication-matcher/run-sync": { "post": { "operationId": "run-sync-junipr-entity-deduplication-matcher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "targets": { "title": "Targets", "type": "array", "description": "Targets to process. Each target can include snapshots, HTML, CSV text, records, and optional source URL.", "items": { "type": "object" }, "default": [] }, "records": { "title": "Inline Records", "type": "array", "description": "Optional structured rows for one target.", "items": { "type": "object" }, "default": [] }, "csvText": { "title": "CSV Text", "type": "string", "description": "Optional CSV text for one target.", "default": "" }, "fetchUrls": { "title": "Fetch URLs", "type": "boolean", "description": "Fetch source URLs over HTTP. Default is false to avoid cloud usage and network variability.", "default": false }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 50, "type": "integer", "description": "Alias for Max Targets/Maximum Records used by the Junipr actor baseline. When both are provided, actor-specific limits still apply.", "default": 1 }, "includeReport": { "title": "Include Report Artifacts", "type": "boolean", "description": "Write JSON summary, JSON results, and Markdown report artifacts to the key-value store.", "default": true }, "maxTargets": { "title": "Max Targets", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum entity batch targets to process.", "default": 1 }, "maxTextBytes": { "title": "Max Text Bytes", "minimum": 1000, "maximum": 2000000, "type": "integer", "description": "Maximum text bytes to analyze per target.", "default": 500000 }, "dryRun": { "title": "Dry Run", "type": "boolean", "description": "Validate input and write a dry-run summary without PPE charges or dataset output.", "default": false }, "debug": { "title": "Debug Logs", "type": "boolean", "description": "Enable debug logs.", "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 } } } } } } } } } } ```