Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours

Abstract

Text classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a classifier generally requires coding skills and ML knowledge, which poses a significant barrier for many potential users. To lift this barrier we introduce Label Sleuth, a free open source system for labeling and creating text classifiers. This system is unique for; (a) being a no-code system, making NLP accessible for non-experts, (b) guiding its users throughout the entire labeling process until they obtain their desired classifier, making the process efficient - from cold start to a classifier in a few hours, (c) being open for configuration and extension by developers. By open sourcing Label Sleuth we hope to build a community of users and developers that will widen the utilization of NLP models.