v1.0.0

• Support for common annotation tasks:
  • Text classification
  • Named entity recognition. Support intersecting and overlapping text labeling as well as a secondary labeling.
  • Tabular classification and regression
  • Images recognition with bounding boxes and polygons
  • Log labeling
• Support label type
  • Text
  • Numeric
  • Upload hierarchical taxonomy file
• Active learning with uncertainly sampling to query unlabeled data. Allow users to choose active learning query strategy and select Spacy models (for different languages and model sizes)
• Project tracking with real time data aggregation and review process
  • Keep track of the progress of every annotator. Annotators are informed if they are not starting the task and not making progress before the entire labelling project is completed.
• User management panel with role-based access control
• Data management
  • Import in common data formats
  • Export in ML friendly formats
  • Data sharing through community datasets
  • Review the labelling quality for Text, Tabular, NER, and Image projects. Project owners can review the annotation, make modification, and pass review. Review assignment logic support most_uncertain, random and sequential.
• Swagger API for programmatic labeling, connecting to data pipelines and more
• Slack integration. Assigning a Text or Tabular project to a Slack channel and all users in the channel can start the annotation task in Slack.