Blog
Evaluating NLP: Assembling a Test Dataset
Part 1 of Evaluating Natural Language Processing for Named Entity Recognition in Six Steps How do you know if a given natural language package will do what you need? How can ...
Learn more
Releases
NEW Release 1.14.0 (August 2019)
NEW Release 1.13.0 (April 2019)
NEW Release 1.12.2 (February 2019)
NEW Release 1.12.1 (January 2019)
Annotating Evaluation Data and Scoring Results for Evaluating NLP
Part 2 of Evaluating Natural Language Processing for Named Entity Recognition in Six Steps In our previous blog post, we discussed the importance of defining your requirements for your NLP evaluation. ...
Learn more
U.S. Customs & Border Protection
U.S. Customs and Border Protection (CBP) provides security and facilitation operations at 328 ports of entry throughout the country. CBP takes a comprehensive approach to border management and control, combining ...
Learn moreDeep Learning Brings Fuzzy English-to-Japanese Name Matching Into Focus
Matching thousands of Latin-based names to their Japanese equivalent is a very specific and troublesome problem. It is one of many “edge cases” (i.e., a specific name matching problem) ...
Learn more
Kanopy
Rosette enables better search of streaming content Introduction A few short years ago, checking out popular DVDs from the library was a new and radical idea. Today library patrons want to “borrow” ...
Learn more
Plus Alpha Consulting
Plus Alpha Consulting enables analysis of customer feedback from Chinese social media with Rosette® Established in 2006, Tokyo-based Plus Alpha Consulting Co., Ltd. specializes in software as a service (SaaS) for ...
Learn moreWelcome to OFAC Compliance, Apple
Name matching failure results in $467,000 fine and delivers a wake-up call for all companies Once upon a time, it seemed only banks and border security had to worry about the ...
Learn more
Toshiba
Since the Sept. 11, 2001 terrorist attacks in the U.S., complying with the need to swiftly screen names against expanding watchlists has become a growing issue. To meet that challenge, ...
Learn moreWhat’s in a Persian Name?
How Persian names are composed from history, social class, religious affiliation, and geographic origins This month we have a special blog post by computational linguist and NLP engineer Zina Saadi. For this ...
Learn moreRosette 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 ...
Learn moreWhat’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 ...
Learn moreCross-Lingual Search Based on Concepts and Meaning
We've recently released this whitepaper which explores a new way to solve cross-lingual semantic search. Rather than use machine translation to translate queries or search records, this approach delivers better ...
Learn moreYou Say Jamāl, He Writes Djamel: Influences on Western Transliteration of Arabic Names
When it comes to name searching and matching, each language poses its own unique challenges. Arabic is one of the most complex languages for name-matching applications to analyze. This article ...
Learn moreHow Data Annotation Works: Inside NLP and Search, Part IV
Interested search technology—or AI generally? Over the next four weeks, we’re going to take an in-depth (and interesting!) look at the technology that makes modern search tick. This week, we're ...
Learn moreWhy Data & Data Annotation Make or Break AI: Inside NLP and Search, Part III
Interested search technology—or AI generally? Over the next four weeks, we’re going to take an in-depth (and interesting!) look at the technology that makes modern search tick. Today we're digging ...
Learn more