How S&P Global is making markets more transparent with NLP, spaCy and ProdigyA case study on S&P Global’s efficient information extraction pipelines for real-time commodities trading insights in a high-security environment.
Introducing spaCy v3.5spaCy v3.5 introduces new CLI commands, fuzzy matching, improvements for entity linking and more.
How Nesta uses NLP to process 7m job ads and shed light on the UK’s labor marketA case study on Nesta’s workflow for extracting 7 million job ads to better understand UK skill demand, using a custom mapping step to match skills to any government taxonomy.
Explosion in 2022: Our Year in ReviewIt's been another exciting year at Explosion! We've developed a new end-to-end neural coref component for spaCy, improved the speed of our CNN pipelines up to 60%, and published new pre-trained pipelines for Finnish, Korean, Swedish and Croatian. We've also released several updates to Prodigy and introduced new recipes to kickstart annotation with zero- or few-shot learning.
Launching the Explosion Merch StoreSpread the love and support us and our open-source work with some of our unique, custom-designed swag. All orders come with free shipping and stickers!
Training spaCy NER Models with ProdigyThis handy flowchart contains our most common tips, tricks, and best practices for training and updating spaCy named entity recognition models with Prodigy.
Introducing spaCy v3.6spaCy v3.6 introduces the span finder component and trained pipelines for Slovenian.
Introducing spaCy v3.4spaCy v3.4 brings typing and speed improvements along with new vectors for English CNN pipelines and new trained pipelines for Croatian.
