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Hay Equipos launches tool to clean and extract article data

By PulseAugur Editorial · [1 sources] ·

Hay Equipos has launched an Article Extractor tool on the Apify Store designed to clean and extract key information from news articles at scale. The tool processes lists of URLs, removing extraneous content like menus and ads to provide only the main article text, title, author, publication date, and other metadata. It utilizes Mozilla Readability for text extraction and parses publisher metadata such as Open Graph and JSON-LD for factual details, ensuring accuracy in the extracted information. The service is priced per article extracted, with failed extractions being free, and offers options for including plain text, Markdown, or cleaned HTML output. AI

IMPACT Streamlines data ingestion for LLM pipelines and RAG systems by providing clean, structured article content.

RANK_REASON Launch of a specific tool for data extraction.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Hay Equipos launches tool to clean and extract article data

How we ranked this

Signal score
1 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Launch of a specific tool for data extraction.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
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Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

Full methodology in our editorial standards.

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Hay Equipos ·

    How to extract clean article text, author and date from news URLs

    <p>Copying an article out of a web page sounds easy until you try it at scale. You get menus, cookie banners, related links and ads mixed into the text, and the author and publish date are hidden in a different place on every site. If you feed that into an LLM, a RAG index or a m…

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