Overview
The NLP Lab product will be officially retired at the end of 2024 and will be replaced by the Generative AI Lab platform. We encourage all NLP Lab users to subscribe to Generative AI Lab to continue enjoying uninterrupted service and to take advantage of its advanced features. Please visit our product page or contact our support team for detailed information on the transition process and subscription options. NLP Lab is a Free End-to-End No-Code platform for annotating text and training AI/ML models. It enables domain experts to extract meaningful facts from text documents, images or PDFs and train models that will automatically predict those facts on new documents. This is done by using state-of-the-art Spark NLP pre-trained models or by tuning models to better handle specific use cases.
About the offer
Based on an auto-scaling architecture powered by Kubernetes, NLP Lab can scale to many teams and projects. Enterprise-grade security is provided for free including support for air-gap environments, zero data sharing, role-based access, full audit trails, MFA, and identity provider integrations. It allows powerful experiments for model training and finetuning, model testing, and model deployment as API endpoints.
There is no limitation on the number of users, projects, tasks, models, or trainings that can be run with this subscription.
Healthcare and Visual features are available via BYOL.
Included Features:
- Annotation support for Text, Image, Audio, Video and HTML content;
- High productivity annotation UI with keyboard shortcuts and pre-annotations;
- Support for text annotation in 250+ languages;
- Out-of-the-box support for the following NLP tasks: Classification, Named Entity Recognition, Assertion Status, and Relation Extraction;
- Support for projects and teams: 30+ project templates; unlimited projects and users, project import, export and cloning, project grouping;
- Task assignment, tagging, and comments; duplicate tasks identification; task searching and filtering;
- Consensus analysis and Inter Annotator Agreement charts;
- Performance dashboards;
- Enterprise-level security and privacy: role-based access control, role-based views, annotation versioning, full audit trail, Single Sign on;
- AI-Assisted Annotation: never start from scratch but reuse existing models to pre-annotate tasks with the latest Spark NLP models for classification, NER, assertion status, and relation detection;
- Full Models Hub integration: you can explore available models and embeddings, download them with the click of a button and reuse those in your project configuration.
- Train Classification, NER, and Assertion Status models: use default parameters or easily tune them on the UI for different experiments;
- Active Learning automatically trains new versions of your models once new annotations are available;
- API access to all features for easy integration into custom data analysis pipelines;
Who is this offer for
- Domain experts (e.g. nurses, doctors, lawyers, accountants, investors, etc.) who want to test DL models on their data or/and tune/train new models via an easy-to-use UI, without writing a line of code;
- Data labeling teams who want to optimize the efficiency and speed of their day-to-day work with preannotations;
- Data scientists who deal with NLP problems;
- Machine Learning engineers who need to test/train/tune NLP models;
- Scientific researcher groups who need to extract meaning from unstructured, natural language documents;
- And anyone else interested in text and image analysis, image digitization, data extraction, document labeling and/or NLP model training.
Technical Specifications
- Recommended memory: 32GB RAM
- Recommended vCPU:8 vCPUs
- Operating System:Ubuntu 20.04
3 Easy Steps to get started
- Subscribe to the product on the AWS Marketplace.
- Deploy it on a new machine.
- Access the login page for a guided experience on http://INSTANCE_IP. For the first login use the following credentials:
- Username: admin
- Password: INSTANCE_ID
Highlights
- Includes everything: - Model Hub Integration - Project Management - Role Based Access - Workflows - Analytics - Model Training and Testing - Preannotations - Security and Privacy Unlimited everything: - Users - Projects - Models - Tasks - Annotations - Pre-annotations - Training
- Features available with BYOL: Healthcare NLP: - Access to 550+ Healthcare pre-trained models covering Clinical and Biomedical NER for 400+ entity types; Assertion Status detection (positive, negative, possible, past and future facts), Clinical Relation Extraction; - De-identification NER Models - Model tuning - Build your models on existing pre-trained models - Programmatic labeling via dictionary and regex-based rules;
- Features available with BYOL: Visual NLP - Pre-annotate PDF and image tasks with Visual NER models; - Tune Visual NER models for your data; - Sticky and custom annotations; - Automatic text recognition; - Support for relation annotation on top of images; - Text-based search on the image/PDF; - Zoom features;
Details
Typical total price
$0.384/hour
Pricing
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
---|---|---|---|
t2.2xlarge | $0.00 | $0.371 | $0.371 |
m5.2xlarge Recommended | $0.00 | $0.384 | $0.384 |
m5.4xlarge | $0.00 | $0.768 | $0.768 |
m5.8xlarge | $0.00 | $1.536 | $1.536 |
m5.12xlarge | $0.00 | $2.304 | $2.304 |
m5.16xlarge | $0.00 | $3.072 | $3.072 |
m5.24xlarge | $0.00 | $4.608 | $4.608 |
m5.metal | $0.00 | $4.608 | $4.608 |
Additional AWS infrastructure costs
Type | Cost |
---|---|
EBS General Purpose SSD (gp2) volumes | $0.10/per GB/month of provisioned storage |
Vendor refund policy
This software is free to use. Users need to pay price to Amazon according to the EC2 instances/servers used.
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
NLP Lab 5.9 introduces significant updates aimed at enriching and expanding the capabilities of your NLP workflows. This release represents a major step forward, offering support for Entity Resolution for standard taxonomies like ICD-10, RxNorm, SNOMED, LOINC, UMLS, MeSH, CPT for both annotations and pre-annotations activities. Furthermore, the inclusion of Rules and Prompts in Visual NER projects enables improved pre-annotation results without the need for trained models. The introduction of the Supervisor role offers enhanced authority compared to the Annotator role. Additionally, the ability to Import and Export projects in S3/Blob further enhances NLP Lab 5.9 for easier project backup and sharing capabilities. These advancements, coupled with our ongoing commitment to performance enhancements and user experience improvements, underscore our dedication to meeting the evolving needs of the NLP community. Discover the limitless possibilities with NLP Lab 5.9 and elevate your NLP projects to new levels of excellence. Detailed descriptions of all new features and improvements are provided below.
https://nlp.johnsnowlabs.com/docs/en/alab/annotation_labs_releases/release_notes_5_9_0
Additional details
Usage instructions
Launch the AMI Annotation Lab will then be served on http://<public ip of instance>
To login use the following credentials
- username: admin
- password: <instance-id from AWS EC2>
Resources
Support
Vendor support
Technical support for NLP Lab by Development Team support@johnsnowlabs.com
John Snow Labs also offers professional services to deliver custom data science work that is specific to your needs. Our team of experts is ready to assist you with various tasks, including training custom AI models, developing machine learning pipelines, annotating documents, creating Python notebooks, generating insightful reports, and much more. Our professional services are specifically designed to help you achieve remarkable results without the steep learning curve or overwhelming workload.
In addition, when you opt for an annual NLP Libraries prepaid subscription you gain access to a host of exclusive benefits:
A dedicated customer success manager A dedicated account manager Four hours of personalized onboarding from our data scientists Year-long customer support on a dedicated Slack channel
Additional Resources:
AWS Marketplace Slack Channel: https://spark-nlp.slack.com/archives/C064YR9NLBX
End-to-End No-Code Development of NER model for Text with NLP Lab: https://www.youtube.com/watch?v=jgUylZlz3uA&ab_channel=JohnSnowLabs
NLP Lab Release Notes:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Must try Annotating Tool
Great annotation tool
Easy and powerful.
With this tool, it is very easy to obtain the first results and start building your projects iteratively.
I liked the support for rules and the fact that I can easily reuse my dictionaries and regexes to create rules and combine them with entity extraction models in the same project.
It is good that it offers support for PDF annotation. A lot of the documents we work with are scans so this can be very useful in our future projects.
Capable & fast Ux/UI
Broad functionality.
Tried & like:
- Images and text
- Text: named entity extraction, classification, relationship annotations.
- Preannotations
- Training of models within Annotation Lab environment.
- Workflow.
- Statistics and internal annotation agreement.
- Background API integration.
- It is free to use (except for the infrastructure). (You have to pay for OCR or healthcare models.)
Cons: You need to pay for EC2 machine when is up (or available for Linux outside of AWS) - not available serverless.
It makes a difference
One of the best tools I have experienced so far in order to support my data annotation and augmentation projects. Highly recommended to be considered to be deployed in your organization