Discover what (or who) we talk about | Entity Extraction

Entity Extraction


Automatically identify the common entity types in your multilingual text, including people, organizations, locations and more

entity extraction

Overview

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 engine

Customizable to your unique needs

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

This can mean training Rosette on a specific type of content, such as news articles, blogs, restaurant reviews, financial documents, medical records, legal contracts, patent filings, or short strings of text like 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

  • 21 supported languages
  • 700+ entity types detected
  • Filter for key entities
  • Confidence scores for each result
  • Cloud or enterprise 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:
Plugins:
Bindings:

Supported Languages

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

Entity Types

Rosette recognizes over 700 entity types and will link to a WikiData QID and DBpedia parse tree when it is available.

As an example: 

“Ibuprofen” will be tagged as “SUBSTANCE”, linked to the WikiData ID: Q186969, and assigned the DBpedia tree ”ChemicalSubstance/Drug”.

Try the Demo

Rosette Cloud

Easy to Use

Built for the most demanding text analytics applications and engineered to deliver high accuracy without sacrificing speed, Rosette Cloud is instantly accessible and offers a variety of plans to suit both startups and enterprises. Our entity extraction endpoint is prebuilt to recognize and extract 700+ entity types with coverage across 21 languages.

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

Get a Rosette Cloud 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 Rosette Cloud endpoints along-side examples in the binding of your choice.

 Visit our GitHub for bindings and documentation.

Enterprise Ready

Evaluate Rosette’s functional fit with your business and data needs on Rosette Cloud knowing that scalable, customizable, enterprise deployments are available if you need them.

{
  "entities": [
    {
      "type": "ORGANIZATION",
      "mention": "Securities and Exchange Commission",
      "normalized": "Securities and Exchange Commission",
      "count": 3,
      "mentionOffsets": [
        {
          "startOffset": 4,
          "endOffset": 38
        },
        {
          "startOffset": 166,
          "endOffset": 169
        },
        {
          "startOffset": 536,
          "endOffset": 539
        }
      ],
      "entityId": "Q953944",
      "confidence": 0.67070782,
      "linkingConfidence": 0.27190905,
      "dbpediaType": "Agent/Organisation/GovernmentAgency"
    },
    {
      "type": "PERSON",
      "mention": "Bridget Fitzpatrick",
      "normalized": "Bridget Fitzpatrick",
      "count": 2,
      "mentionOffsets": [
        {
          "startOffset": 99,
          "endOffset": 118
        },
        {
          "startOffset": 287,
          "endOffset": 298
        }
      ],
      "entityId": "T1",
      "confidence": 0.92063326
    },
    {
      "type": "PERSON",
      "mention": "David Gottesman",
      "normalized": "David Gottesman",
      "count": 2,
      "mentionOffsets": [
        {
          "startOffset": 174,
          "endOffset": 189
        },
        {
          "startOffset": 307,
          "endOffset": 316
        }
      ],
      "entityId": "Q5234268",
      "confidence": 0.92488831,
      "linkingConfidence": 0.47211223,
      "dbpediaType": "Agent/Person"
    },
    {
      "type": "TITLE",
      "mention": "Chief Litigation Counsel",
      "normalized": "Chief Litigation Counsel",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 134,
          "endOffset": 158
        }
      ],
      "entityId": "T2",
      "confidence": 0.3306601
    },
    {
      "type": "TITLE",
      "mention": "Deputy Chief Litigation Counsel",
      "normalized": "Deputy Chief Litigation Counsel",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 229,
          "endOffset": 260
        }
      ],
      "entityId": "T5",
      "confidence": 0.81287289
    },
    {
      "type": "TEMPORAL:DATE",
      "mention": "December 2016",
      "normalized": "December 2016",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 268,
          "endOffset": 281
        }
      ],
      "entityId": "T6"
    },
    {
      "type": "TITLE",
      "mention": "Ms.",
      "normalized": "Ms.",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 283,
          "endOffset": 286
        }
      ],
      "entityId": "T7",
      "confidence": 0.76600134
    },
    {
      "type": "TITLE",
      "mention": "Mr.",
      "normalized": "Mr.",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 303,
          "endOffset": 306
        }
      ],
      "entityId": "T9",
      "confidence": 0.72353458
    },
    {
      "type": "TITLE",
      "mention": "Co-Acting Chief Litigation Counsel",
      "normalized": "Co-Acting Chief Litigation Counsel",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 332,
          "endOffset": 366
        }
      ],
      "entityId": "T11",
      "confidence": 0.03582656
    },
    {
      "type": "LOCATION",
      "mention": "Washington D.C.",
      "normalized": "Washington D.C.",
      "count": 1,
      "mentionOffsets": [
        {
          "startOffset": 460,
          "endOffset": 475
        }
      ],
      "entityId": "Q61",
      "linkingConfidence": 0.66086622,
      "dbpediaType": "Place/PopulatedPlace/Settlement"
    }
  ]
}

Rosette Enterprise

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 deployments 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.

Request a Free Product Evaluation

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

Drop Us a Line

EMAIL:
info@basistech.com

PHONE:
+1-617-386-2000

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