Tag: Entity Linking

Rosette 1.14 Release: Entity linking to Thomson Reuters PermID, Multi-model language identification

The August release of Rosette 1.14 brings new features to entity extraction and linking, as well as language identification. Roadmap for linking entities to multiple knowledge bases In addition to linking to entities in Wikidata and DBpedia, entity extraction Rosette will ultimately link to multiple knowledge bases, including Thomson Reuters open PermID. PermID covers a […]

What’s the Difference Between Entity Extraction (NER) and Entity Resolution?

Entity extraction, or named entity recognition (NER), is finding mentions of key “things” (aka “entities”) such as people, places, organizations, dates, and time within text. Entity mentions are the words in text that refer to entities, such as “Bill Clinton,” “White House,” and “U.S.” Entity resolution (aka, entity linking) takes it one step further and […]

Rosette Cloud 1.12: New Languages for Entity Linking, Better Korean Named Entity Extraction, and Delivery via Docker!

We’re thrilled to announce the latest version of Rosette (1.12). This release features many exciting updates to our text analytics platform, including expanded language coverage, better accuracy, as well as new options for software delivery. Entities: Linking expanded to more languages and better Korean We’ve devoted a lot of focus to improving our support for […]

Rosette Cloud 1.11: New Entity Types, Hungarian Names, and Cross Language Semantics

We’re thrilled to announce the latest version of Rosette (1.11). It’s a big one — lots of exciting new features, enhancements, and improvements. We hope you’ll check it out! TL; DR check the release notes. Entities: Enhanced Extraction and Linking with New Types Rosette Entity Extraction & Linking now recognizes 700 new classes of entities […]

Provide Live Feedback to Your Entity Linking Knowledge Bases

Rosette Entity Linking adds real-time, human-in-the-loop feature to entity linking databases While entity extraction provides the foundation of data mining and information extraction systems, extracted entities only have limited value out of context. Understanding not just what entity strings are included in your data but also the real-world entity they link back to is vital […]

Understanding the Difference Between Open and Targeted Relationship Extraction

Who’s in your data, and how are they connected? You may have heard about relationship extraction and wondered what this NLP innovation is. Relationship extraction is the automated detection and classification of semantic relationships between entities in text. It goes beyond automatically adding metadata to articles, to “writing” profiles and reports about a person, place, […]

Rosette Cloud 1.9: More Languages, Higher Accuracy, and Deep Neural Nets

Rosette Cloud 1.9 is out, delivering a new language for name matching, translation, and deduplication: Thai. We’ve also added a new deep neural network model for sentiment analysis, entity extraction offsets, salience scores for topic extraction, and more. Learn more below, or jump to the release notes. Name Matching The /name-similarity, /name-translation, and /name-deduplication endpoints […]

Just the Important Entities, Please

Salience scores and linking confidence scores for extracted entities come to Rosette Cloud Data scraped from the web is often very noisy and cumbersome to work with. Sorting through it to find the most valuable information is a vital step in converting raw data into actionable insights. The release of Rosette Cloud 1.8 aims to […]

Not-So-Cheap Talk: Stocks Move Nearly 10% When Trump’s Tweets Mention Executives

Prattle is a Fintech innovator whose system started by forecasting market reactions to central bank communications. As a member of the Basis Technology startup program Prattle uses Rosette entity extraction to detect the speakers in central bank communications. They’ve since expanded to power analyses like the blog post below: Despite what the financial press might […]