The Ambiverse Natural Language Understanding API (NLU API) is capable of automatically identifying entities such as people, locations, organizations, or products in text. The task is not trivial since many entities are usually referred to with the same name. The name "Paris", for instance, may refer to cities in France, USA, or Argentina, or to people like Paris Hilton, mythological figures like Paris, prince of Troy, among many others.
Identifying entity references in text provides multiple applications in the news domain bringing digital content into the linked data publishing era.
Improve the News Reading Experience
Linking person and organization names to background information improves the users’ reading experience by giving them more information: either reference information or related articles relevant for the entity in question.
Increase the User Visit Duration
Links in text to related articles and background information on your site increase the users' visit duration, leading to increased monetization potential.
Optimize Your Content for Search Engines
Linking names in articles to relevant sources (e.g. Wikipedia or your archive) connect your content to the linked data world. Links to authoritative pages are a key element in search engine optimization, increasing your site's credibility.
Give Your Archived Content More Visibility
News portals are full of content. Especially older content gets buried quickly. Tags make your content visible and reachable, and entities make great tags.