Entity Extraction — often known as named-entity recognition — engines in the Veritone cognitive engine ecosystem classify words and phrases found in unstructured text into predefined categories, such as people, organizations, and locations.
Entity extraction cognitive engines can also denote the time or date which assists during pre-processing large volumes of data.
Entity Extraction Features:
- Pre-Trained Entity Library
Label words, phrases, and concepts text by people, places, organizations, locations, product, title, nationality, religion, credit card number, email address, money, personal identification numbers, URL, dates, time, distance, longitude and latitude, and more to support diverse, time-saving use cases.
- Near Real-Time Processing
Process text files in near real-time for use cases requiring entity extraction fast and at scale.
- Long-Form Text Support
Classify short-form or long-form text files.
- Flexible Deployment
Deploy in a new or integrate into an existing application in the cloud via aiWARE GraphQL APIs, or with a subset that can be deployed on-premise via a Docker container. Learn more.
- Powered by an AI Ecosystem
Leverage advanced entity extraction machine learning algorithms from the Veritone managed cognitive engine ecosystem — including algorithms from Veritone, niche providers, and industry giants.