# Facebook Page Identity Resolver & URL Deduplicator (`mentat-logic/mentat-resolver`) Actor Unify Facebook page URL variants into one canonical identity and remove duplicate posts from any scraper export. Free. Never guesses — unresolved rows carry their evidence. - **URL**: https://apify.com/mentat-logic/mentat-resolver.md - **Developed by:** [Mentat Logic](https://apify.com/mentat-logic) (community) - **Categories:** Developer tools - **Stats:** 3 total users, 0 monthly users, 80.0% runs succeeded, 0 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Facebook Page Identity Resolver & URL Deduplicator **Free utility by Mentat Logic.** Feed it the output of any Facebook posts scraper — it tells you which rows belong to which page (one canonical identity per page, however many URL styles the scraper produced) and removes duplicate posts. Clean input for any analysis you run next. ### The problem it solves The same Facebook page arrives from scrapers under many names: `m.facebook.com/SomePage`, `www.facebook.com/somepage/`, `facebook.com/profile.php?id=1000…`, `facebook.com/p/Some-Page-1000…`. The same post arrives with and without tracking parameters. Count anything before resolving identity and your numbers are wrong. ### What it does - **Canonical page identity** — unifies m./www./web. hosts, `profile.php?id=`, `/p/Name-ID/`, legacy `/pages/Name/ID`, and slug case into one stable id (`fb:slug` or `fb:numeric-id`; groups as `fbgroup:…`). - **Post URL deduplication** — strips tracking parameters (keeps `story_fbid`/`id`), unifies hosts, and counts each post once. - **Format detection** — recognizes the official `apify/facebook-posts-scraper` export (verified field mapping) and falls back to a generic mapper for other exports. The output always states which mapping was used. ### What it deliberately does NOT do - **It never guesses.** A URL that doesn't carry page identity (a `/watch` link, a bare post URL, a non-Facebook domain) is reported as *unresolved with its evidence* — not silently merged, not silently dropped. - It does not call Facebook, does not scrape, does not enrich. It reads only the dataset you point it at, in your own account. - Absent fields stay absent. Nothing is filled with zeros. ### Input Any one of: a **dataset ID** from your account · **raw JSON items** pasted directly · a **plain list of page URLs**. Run with no input at all and it processes a small built-in synthetic sample so you can see the output shape. ### Output (dataset items) 1. One `summary` item — rows in, format detected, unique posts, duplicates removed, pages resolved, unresolved count. 2. One `page` item per canonical identity — id, name, every URL variant observed, post count. 3. `unresolved` items — each with the reason and the evidence. 4. Optionally one `post` item per unique post (canonical URL + text head). ### See what it returns Real output of the built-in demo run — including the duplicate it caught and the same-name pair it refused to merge: ![Demo output](https://mariusmarcovici-cpu.github.io/mentat-assets/resolver_output.png) [Open the full sample output →](https://mariusmarcovici-cpu.github.io/mentat-assets/resolver_output_preview.html) (run it yourself with empty input — free, 3 seconds) 📖 Background: [The Facebook URL Zoo — every page-link format and how to canonicalize them](https://dev.to/mentat_logic/the-facebook-url-zoo-every-page-link-format-and-how-to-canonicalize-them-4jfe) — the reference article behind this tool’s rules. ### Price Free — no developer fee. You pay only your own Apify compute. If it saves you a bad number, look at our other tools. ### Permissions, stated plainly This Actor requests full permissions for one reason: to read the dataset ID you point it at. It writes only to its own run storage. It never modifies, deletes, or reads anything else in your account. --- *Mentat Logic — analysis tools that state their coverage, show their working, and render the unknown as unknown.* # Actor input Schema ## `datasetId` (type: `string`): ID of a dataset in YOUR Apify account produced by any Facebook posts scraper. Leave everything empty to run the built-in synthetic demo. ## `items` (type: `array`): Alternatively: paste the scraper output directly as a JSON array of post objects. ## `urls` (type: `array`): Alternatively: a plain list of Facebook page URLs to canonicalize. ## `includePosts` (type: `boolean`): Also emit one item per unique post. Turn off for identity-only output. ## Actor input object example ```json { "includePosts": true } ```` # Actor output Schema ## `results` (type: `string`): No description # 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("mentat-logic/mentat-resolver").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("mentat-logic/mentat-resolver").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 mentat-logic/mentat-resolver --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mentat-logic/mentat-resolver", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Page Identity Resolver & URL Deduplicator", "description": "Unify Facebook page URL variants into one canonical identity and remove duplicate posts from any scraper export. Free. Never guesses — unresolved rows carry their evidence.", "version": "0.0", "x-build-id": "VFmrMKQbihTHCZ1dn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mentat-logic~mentat-resolver/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mentat-logic-mentat-resolver", "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/mentat-logic~mentat-resolver/runs": { "post": { "operationId": "runs-sync-mentat-logic-mentat-resolver", "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/mentat-logic~mentat-resolver/run-sync": { "post": { "operationId": "run-sync-mentat-logic-mentat-resolver", "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": { "datasetId": { "title": "Dataset ID", "type": "string", "description": "ID of a dataset in YOUR Apify account produced by any Facebook posts scraper. Leave everything empty to run the built-in synthetic demo." }, "items": { "title": "Raw items (JSON)", "type": "array", "description": "Alternatively: paste the scraper output directly as a JSON array of post objects." }, "urls": { "title": "Page URLs", "type": "array", "description": "Alternatively: a plain list of Facebook page URLs to canonicalize.", "items": { "type": "string" } }, "includePosts": { "title": "Output deduplicated posts", "type": "boolean", "description": "Also emit one item per unique post. Turn off for identity-only output.", "default": true } } }, "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 } } } } } } } } } } ```