coloured pencils arranged in a row for readership
Twitter
Facebook
LinkedIn

Topics and Entities

Decode Media with Topics and Entities

Ready to transform how you extract insights from news articles? Opoint’s Topics and Entities feature offers a groundbreaking way to extract valuable insights from news articles in real-time.

Simplify Complexity with Advanced Technology

We’ve teamed up with a leading tech firm in the UK to bring you a solution that combines state-of-the-art natural language processing with real-world data. The result? Efficient and accurate extraction of topics, events, and entities from news articles. 

Real-Time Metadata, Real Results

Our Topics and Entities feature integrates seamlessly into your Opoint news feed, whether you’re using an API or Feed. This real-time metadata transforms your approach to news data analysis.

Get the Full Story

Dive into Topics

With our integration of the International Press Telecommunications Council (IPTC) Media Topics, you get a comprehensive taxonomy of over 1,200 terms designed for media content categorisation.  
And the best part? We can create feeds based on these topics for even more targeted analysis.

Uncover Key Players

To fully grasp the impact of news articles, it’s essential to identify the entities involved. Our technology scans entire articles, pinpointing all relevant persons, locations, and organisations. Advanced techniques ensure you get a clear picture of the key players in the news landscape. 

Product Details

Topics

The International Press Telecommunications Council (IPTC) was established in 1965, and its primary focus is to develop and promote industry standards for the exchange of news data.

We have chosen the IPTC Media Topics as our default taxonomy. It is a constantly updated taxonomy of over 1,200 terms developed specifically for the categorisation of media content, and it is updated at least once a year.

Topic tags include:

  • Label – the name of the IPTC Media Topic
  • Media Topic ID – the unique IPTC Media Code
  • Score – the overall confidence that the article revolves around the topic.

 

Entities

We analyse the entire article to identify all persons, locations, and organisations. The process includes advanced disambiguation to avoid delivering duplicate entities.

Entity tags include:

  • Entity type – person, location, or organisation
  • Entity – name of person, location, or organisation
  • Wikidata ID – a link to additional information about the entity (when possible).

Subscribe to our newsletter

Read more about Topics & Entities

Opoint filters the news and lets you detect unseen patterns in news data. Download this document to find how we extract topics and named entities from news articles in real-time.

Related

James Hannan

Ready to see our solutions in action?

James Hannan

Book your free, customised demo today.

Download