#InformationExtraction

Live, measured metrics for the hashtag #InformationExtraction from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

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Own #informationextraction

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$5.00/ year · 21-character #name
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1
Uses / 7 days
Mastodon
1
Accounts / 7 days
Mastodon
23
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 23
0.5
Avg reactions / post
Mastodon · last 23

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 14:48 UTC
0
07-21
1
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

1 uses by 1 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 14:48 UTC

No related tags with measured usage found for #informationextraction.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 14:48 UTC

Everything below is measured over the latest 23 public posts (spanning ~36998 hours).

Posting hours (UTC) — busiest: 08:00

00:0012:0023:00

Languages: English (20) · German (3)

Avg boosts / post: 2.7

Top of the latest posts

  • Open PhD/Junior Researcher Position in Neurosymbolic AI and Information Extraction on historical documents at FIZ Karlsruhe - Knowledge-driven AI research group (former ISE research group), starting at Jan 1, 2026. Application Deadline: Oct

    Harald Sack@[email protected]♥ 5↻ 82025-10-10 08:33 UTCView post →

  • Today, I'm at Bundesarchiv in Koblenz for the Strategy & Planning meeting of our project "Wiedergutmachung". Our task in this project is to develop efficient information extraction from historical case files of the German Postwar recompensa

    Harald Sack@[email protected]♥ 4↻ 42025-10-14 09:44 UTCView post →

  • GOT (General OCR Theory) is a 580M end-to-end OCR-2.0 model now on Hugging Face 🤗 "GOT consists of a Vision-Encoder to convert images into transformers images into tokens and a decoder for generating OCR outputs in various formats (e.g., p

    Harald Sack@[email protected]♥ 1↻ 72024-09-13 13:13 UTCView post →

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/informationextraction