Entity extraction helps you answer who it is quickly, accurately and concisely Rosette Entity Extractor is a component within Rosette® by Babel Street that automatically identifies and extracts entities from multilingual text. It supports a wide range (19+) of entity types, including people, organizations, locations, dates, nationalities, and more — including custom entity types. Entity Extractor uses machine learning algorithms, entity lists (gazetteers) and regular expressions (pattern matching) to analyze text data and extract entity information. It can identify entities in text and categor ..read more

While the U.S. federal government is developing and adopting new technologies at an unprecedented pace, it’s still challenging to capitalize on commercial innovation without loosening critical security and compliance controls. In part 1 of this two-part series, we first look at how the intelligence community can embrace emerging technologies from the commercial sector and build trust while protecting classified data. In part 2, we’ll examine approaches our national security agencies and commercial technology innovators can take to work together effectively. We asked three former senior officia ..read more

Entity recognition helps link persons and organizations to the agency knowledge base The unknown “unknowns” keep law enforcement and intelligence professionals awake at night. They worry about unknown key actors and the connections between seemingly unrelated cases. If known, the connections would reveal a larger view and possibly a faster, better way to tackle the case. To meet this challenge, named entity recognition (also called entity extraction) links people, organizations, and places found in data to entries in a common investigative knowledge base. This is how AI can reveal the unknowns ..read more

What is adverse media screening? Adverse media screening (AMS), also known as adverse media monitoring, is the process of querying global, reputable news sources for relevant information on clients and prospects who may pose an increased risk to financial institution (FIs). Conducted at client onboarding and periodically thereafter, adverse media screening has become a vital part of financial sector customer due diligence (CDD). In an ongoing effort to halt money laundering and other financial crimes, many regulatory bodies around the world increasingly recommend AMS. The Financial Action Task ..read more

By: Eugene Reyes and Tina Lieu Attorneys performing multilingual eDiscovery face the constant challenge of having  too much data for humans to review. With particularly large volumes of text, it is prohibitively expensive to translate everything. Rosette®  and Linguistic Systems Inc. (LSI) tackled that challenge in a legal case and achieved astonishing results. The answer combined the AI-powered text analytics of Rosette by Babel Street with Ai Translate by LSI — a translation software that uses AI in tandem with expert human translators. (Watch the webinar recording about this proje ..read more

Remember playing “Concentration” as a kid? It’s a tile-match game. Each player must turn over two tiles and remember their placement to win future rounds. It’s a strict match/no match scenario. The red chair matches the other red chair, not the refrigerator. The chicken matches the other chicken, not the xylophone. Name matching works nothing like this. You rarely find an exact chicken-to-chicken match. Nor are mismatches as clear as chicken-to-xylophone. High-velocity, high-stakes name matching in finance, national security, and other industries feels more like uncovering a tile picturing a c ..read more

Everybody loves games, which is why word games are such a valuable way to demonstrate NLP concepts. At Hackathon 2022, Team 3 decided to create their own Rosette -powered guess-the-word game based on semantic similarity.  From left to right: Ethan Roseman, Fiona Hasanaj, Chini Sinha, Ian Redpath, Harjas Sarna The current word game craze was started by Josh Wardle when he created Wordle in 2021. Even if you haven’t played it, you’ve still probably heard of this game, which gives you six chances to guess a new five-letter word each day. After each guess, the game provides feedback based on ..read more

In the world of natural language processing, the strength of a model is limited by the quantity and quality of the data that goes into developing that model. Collecting enough of this data, whether it’s for training or evaluation, can be an overwhelming undertaking for human beings. But what if we could generate a portion of this data automatically? During Hackathon 2022, two teams worked on developing tools to do exactly that.  Team 6 focused on the training data side of things, aiming to improve Rosette’s ability to generalize, or adapt to different domains, with less manual annotation ..read more

It’s safe to say that every piece of human-facing software needs to be intelligible to humans. As far as technology has come, humans and computers still speak very different languages (or, at least, prefer different languages). Just as programmers have to learn languages like Python and JavaScript, software users often need an interpreter to help elucidate raw data. Team 1’s Hackathon 2022 project, an improved visual annotation data model for the entity extraction capabilities of Rosette, is a prime example of this. Rosette stores all data pertaining to its analysis of a document (tokens, enti ..read more

New research from BasisTech may improve entity disambiguation. It posits innovative ways for software to more easily and cost-effectively recognize and disambiguate entities that appear in disparate data streams. The goal is to connect those entities to known entries in an organization’s knowledge base. These connections are vitally important to anti-fraud efforts, government intelligence, law enforcement, and general business processes. This post will examine the need for entity disambiguation, disambiguation challenges, and how BasisTech research may help address those challenges. Understand ..read more