We’re excited to announce the closed beta of our Natural Language Processing (NLP) product: a brand new Named Entity recognition (NER) and text classification labeling system.
Labelbox customers are among the largest enterprises that are rapidly growing their machine learning practices and want a unified platform to create and manage all of their training data. A lot of their real-world machine learning problems require both computer vision and natural language processing models to work in conjunction. Take medical imaging diagnosis for instance; the computer vision model identifies an area of disease and the NLP model subsequently identifies important signals from a patient’s history, which is often stored as text. Both systems need to work together in close tandem to create high-confidence decisions.
The NLP product supports labeling overlapping entities, nested classifications, label analytics, automation, and quality control. Some of these features are still underway, but we’d love to give early access to users willing to provide feedback and help shape the product roadmap.
Sign up here to get early access to NLP (beta) in Labelbox.