Annotation Lab is now the NLP Lab – the Free No-Code AI by John Snow Labs
We are pleased to announce the release of Annotation Lab version 2.2.
This version increases the number of models available on the Models Hub page for preannotation, supports the uploading of an image file (or multiple images zipped) from your computer. It also implements lots of improvements for the Visual NER Project and Labeling Page, as well as UI enhancements and fixed known issues.
Relation Extraction and Assertion Status Models
Users can easily use Relation Extraction and Assertion Status Models for preannotation jobs. A valid Spark NLP for HealthCare License is needed to download them from the Models Hub page. After that as with other models, users can directly use them in the Project Config and deploy a model server.
Download and load relation extraction model
Preannotate using downloaded relation extraction model
Assertion Status Model
Preannotating Assertion statuses are also exactly the same as it is done for other project types. First, an admin user needs to download models from Models Hub and then Project Owner or Manager should configure Assertion Labels using the following two attributes:
- add assertion=”true” attribute to indicate any Label as Assertion Status
- add another attribute to associate the name of the model with the Label using model=”assertion_model_name”
Once it is deployed along with NER model(s), hit the preannotate button on one or more tasks from the Task List page.
With the addition of these two types, now Annotation Lab supports all of the following types of models for preannotation.
- Named Entity Recognition Models (Free/Paid)
- Classification Models (Free/Paid)
- Assertion Status Models (Paid Only)
- Relation Extraction Models (Paid Only)
- Embeddings (Free/Paid)
Local Images Upload
Until this version, only images from remote URLs could be uploaded for Image projects. With this version, the Annotation Lab supports uploading images from your local storage/computer. It is possible to either import one image or multiple images by zipping them together. It is possible for the upload to fail due to the file size being limited to 16 MB. If you need to upload files exceeding the default configuration, please contact your system administrator who will change the limit size in the installation artifact and run the upgrade script.
Our previous version of Annotation Lab introduced Visual NER Labeling Project. The current version improved functionality around this feature. A sample task can be imported from the Import page by clicking the “Add Sample Task” button. Also, the default config for the Visual NER project contains a zoom feature that supports the maximum possible width for low-resolution images when zooming.
Improved Relation Labeling
Creating numerous relations in a single task can look a bit clumsy. The limited space in the Labeling screen, the relation arrows, and different relation types all at once could create difficulty to visualize them properly. We improved the UX for this feature:
- Spaces between two lines if relations are present
- Ability to Filter by certain relations
- When hovered on one relation, only that is focused