Rosette Entity Extractor

A scalable solution for identifying the common entity types in your multilingual text, including people, organizations, locations and more


Things, not strings

Entities are the key actors in your text data: the organizations, people, locations, products, dates and more that are mentioned in your unstructured content. Rosette uncovers these entities, delivering structure, clarity, and insight to your data with adaptability, easy deployment and consistent accuracy and performance across a broad array of languages and text genres.

Rosette uses a synthesis of machine learning techniques including perceptrons, support vector machines, word embeddings, and deep neural networks to balance performance and accuracy.

Real world applications

Entity extraction is the foundation for applications in e-discovery, social media analysis, financial compliance and government intelligence. Rosette allows you to:

  • Resolve a person’s identity for government security and fraud detection
  • Track customer sentiment around products and companies
  • Analyze research for patent law, legal discovery, and compliance
  • Exploit valuable information from open source intelligence
  • Provide targeted search for content publishers and recommendation engines

Customizable to your unique needs

Our entity extractor is highly adaptable. In addition to supervised training, our field training kits enable you to run unsupervised training on your data to create personalized entity extraction models for your use case.

Customizable means training our entity extractor on your content, whether it is news articles, blogs, restaurant reviews, financial documents, medical records, legal contracts, patent filings, or short texts, such as tweets. It can also involve creating new entity types beyond our pre-built list, such as disease and drug names for a medical extractor, or job titles and skills for resume evaluation.

Product Highlights

  • 20 supported languages
  • 18 entity types detected
  • Filter for key entities
  • Confidence scores for each result
  • On-premise or cloud deployments
  • Fast and scalable
  • Industrial-strength support
  • Constantly stress-tested and improved

How It Works

Hybrid approach balances performance and accuracy

For each entity type extracted, we choose the approach that will produce the best results. Rosette combines advanced statistical modeling and neural networks, complemented by regular expressions pattern matching and entity lists. This hybrid system has the flexibility to detect entities missed by more simplistic solutions, improving precision and recall.

Machine learning

Statistical modeling finds entities based on the context, not rote matching of strings or patterns. For that reason, only high-quality training data will yield superior results. Rosette’s models are trained on a carefully curated corpus of millions of news articles, social media platforms, and blog posts. Our in-house team thoroughly tags and annotates the data by native speakers.

Gazetteers and entity lists

Unlike a home-brew or academic extractor, our gazetteers are regularly updated and stress-tested for enterprise level speed and performance. With customers across industry and government, Rosette Entity Extractor can support gazetteers of several million entries with high performance.

Custom entity lists or gazetteers, available to on-premise customers, can be added when users know specific words or phrases that they expect to discover in their data. For example, a clothing manufacturer may add a list of basic colors they’d like to extract from tweets.

Pattern matching

Rules expressed as regular expressions find entities which follow a pattern, such as dates, times, and email addresses. Many standard string patterns are pre-built into our entity extractor, and on-premise customers can easily customize their extraction workflow by editing or adding rules based on their specific needs.

Customization in the field

For use cases where every additional point of accuracy is critical, or for domain-specific entity types, we offer customization tools and services for on-premise deployments. Within Rosette, you can add new entity types or boost your results:

  • Add/edit entity lists
  • Add/edit regular expressions matching
  • Re-train statistical models
    • Unsupervised training for greater accuracy on your data
    • Supervised training for yet greater accuracy or adding new entity types

Tech Specs

Availability and Platform Support

Deployment Availability:

Supported Languages

Arabic French Japanese Portuguese
Chinese, Simplified German Korean Russian
Chinese, Traditional Hebrew Malay Spanish
Dutch Indonesian Pashto Urdu
English Italian Persian Vietnamese

Entity Types

Person Nationality Number Distance
Location Religion ID Number Date
Organization Money Phone Time
Product Credit Card E-Mail Lat/Long
Title URL

Try the Demo

Cloud API

Easy to Use API

Ideal for product evaluation, academic research, and smaller, cost-conscious businesses, our fast and powerful API is instantly accessible and free to get started. Our entity extraction endpoint is prebuilt to recognize and extract 18 entity types with coverage across 20 languages.

Try entity extraction and the rest of Rosette API’s endpoints, free up to 10,000 calls/month!

Get an API Key

Quality Documentation and Support

Customers love our thorough and responsive support team. We also provide in-depth documentation that lists all the features and functions of the various API endpoints along-side examples in the binding of your choice.

Visit our GitHub for the binding and documentation.

Enterprise Ready

Evaluate Rosette’s functional fit with your business and data needs on our cloud API knowing that scalable, customizable, on-premise deployments are available if you need them.

  "entities": [
      "type": "PERSON",
      "mention": "Bill Murray",
      "normalized": "Bill Murray",
      "count": 1,
      "entityId": "Q29250",
      "confidence": 0.9990000128746033
      "type": "PRODUCT",
      "mention": "Ghostbusters",
      "normalized": "Ghostbusters",
      "count": 1,
      "entityId": "Q108745"
      "type": "TITLE",
      "mention": "Dr.",
      "normalized": "Dr.",
      "count": 1,
      "entityId": "T2",
      "confidence": 0.9990000128746033
      "type": "PERSON",
      "mention": "Peter Venkman",
      "normalized": "Peter Venkman",
      "count": 1,
      "entityId": "Q2483011",
      "confidence": 0.9990000128746033
      "type": "LOCATION",
      "mention": "Boston",
      "normalized": "Boston",
      "count": 1,
      "entityId": "Q100"
      "type": "IDENTIFIER:URL",
      "mention": "",
      "normalized": "",
      "count": 1,
      "entityId": "T5"

On Premise

Customize and scale your entity extraction on premise

For organizations with vast data quantities, unique integration needs, and data security restrictions, we provide on-premise API deployment and SDKs to be hosted on your internal servers. Our field training kits enable you to run unsupervised training on your own data to create personalized entity extraction models for your use case, or create custom entity types beyond the 18 prebuilt entities.

Request a Free Product Evaluation

If your organization requires an on-premise solution, we’re happy to work with you to meet your business’ unique needs. For free evaluation of our on-premise deployments please complete the form below and our Customer Engineering team will provide you with an on-premise evaluation package.

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