Wikipedia Knowledge Base Tracker

Company knowledge-base tracking with source-linked Wikipedia data from the Dataville API

Live article data via Dataville · simulated edit stream · 12 entities monitored

Entities

Edits

Risk Flags

KB Refreshes

Featured use case

Wikipedia Knowledge Base Refresh

Query Wikipedia articles through the Dataville API and get structured, source-linked article content ready for knowledge-base pipelines. The edit stream below shows the kind of change event you'd build on top — founding year, product, controversy and executive changes — to trigger a knowledge-base refresh.

Why use Dataville

One API call returns clean, structured Wikipedia article content — no dumps, scraping or wikitext parsing
Kept fresh from Wikimedia Enterprise snapshots plus hourly update batches, so you run no ingestion
Every response carries its source URL, license and attribution, ready to cite
The same key and response shape for SEC EDGAR and every other Dataville source

Data source

Live (Dataville API): Article text, abstract, categories, last-edit time, license and attribution
Simulated: The edit event stream and its signals, to show the webhook payload you would build
Curated: Risk categories, hand-picked per company for this demo
Payload: The unmodified response from GET api.dataville.com/wiki/{title}

Wikipedia on Dataville API reference Quickstart on GitHub Get a free API key

Edit Stream (simulated)

Simulated events showing the payload shape; not real Wikipedia edits

Running

Monitored Entities

Last Wikipedia edit is live from Dataville; edit counts come from the simulated stream. Click a company to view its payload.

Apple Inc.

2 flags

Technology · edited on Wikipedia —

sim. edits

Alphabet Inc.

3 flags

Technology · edited on Wikipedia —

sim. edits

Microsoft

1 flag

Technology · edited on Wikipedia —

sim. edits

Amazon

2 flags

E-commerce · edited on Wikipedia —

sim. edits

Meta Platforms

3 flags

Social Media · edited on Wikipedia —

sim. edits

Tesla

2 flags

Automotive / EV · edited on Wikipedia —

sim. edits

OpenAI

AI · edited on Wikipedia —

sim. edits

Nvidia

2 flags

Semiconductors · edited on Wikipedia —

sim. edits

Uber

2 flags

Ridesharing · edited on Wikipedia —

sim. edits

Airbnb

1 flag

Hospitality · edited on Wikipedia —

sim. edits

Salesforce

SaaS · edited on Wikipedia —

sim. edits

Netflix

Streaming · edited on Wikipedia —

sim. edits

Risk Flags

Curated risk categories per company (demo data, not derived from the API)

high risk · 9

Apple Inc.

Antitrust cases

high

Alphabet Inc.

Antitrust cases

high

Alphabet Inc.

Privacy controversies

high

Amazon

Labor disputes

high

Meta Platforms

Privacy controversies

high

Meta Platforms

Data breach incidents

high

Tesla

SEC investigations

high

Nvidia

Export controls

high

Uber

Labor disputes

high

medium risk · 8

Apple Inc.

App Store controversies

medium

Alphabet Inc.

Data breach incidents

medium

Microsoft

Antitrust cases

medium

Amazon

Antitrust cases

medium

Meta Platforms

Antitrust cases

medium

Tesla

Tesla controversies

medium

Uber

Regulatory issues

medium

Airbnb

Regulatory issues

medium

low risk · 1

Nvidia

Antitrust cases

low

Article Payload

Live response from the Dataville Wikipedia API

GETapi.dataville.com/wiki/Apple%20Inc.

Source: Wikipedia via the Dataville APIapi.dataville.com