Sold by: Waltsoft Inc.
Deployed on AWS
dslim/bert-base-NER on SageMaker. F1 91.3 on CoNLL-2003. Extracts PER, ORG, LOC, MISC entities in your own VPC -- no data leaving your account, flat $0.08/hr.
Overview
dslim/bert-base-NER is a BERT-base model fine-tuned for Named Entity Recognition on the CoNLL-2003 English dataset, achieving F1 91.3 on the test set. It identifies four entity types: PER (persons), ORG (organizations), LOC (locations), and MISC (miscellaneous named entities).
Deploy as a SageMaker endpoint for in-VPC PII detection, document tagging, and entity extraction at scale. Unlike Amazon Comprehend, this endpoint has no per-character pricing -- you pay a flat $0.08/hr regardless of how many documents you process, making it cost-effective for high-volume extraction over internal document stores.
The endpoint returns character-offset entity spans with entity type and confidence score. Span merging for multi-token entities is handled in the endpoint's inference.py using HuggingFace's aggregation_strategy="simple" to ensure clean entity boundaries.
Primary use cases: PII detection and redaction before storing customer documents, entity-based document indexing for search, contract analysis (extract party names, organizations, locations), compliance screening, and any pipeline that needs to identify and tag named entities at scale without sending data to external services.
Highlights
- F1 91.3 on CoNLL-2003 -- production-grade NER for PER, ORG, LOC, MISC entities, all inference in your AWS VPC
- No per-character pricing unlike Comprehend -- flat $0.08/hr whether you process 100 or 100,000 documents per hour
- Returns character-offset entity spans with confidence scores -- ready for PII redaction, document tagging, and contract analysis
Details
Sold by
Categories
Delivery method
Latest version
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.10 |
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $0.10 |
Vendor refund policy
No refunds.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial release
Additional details
Inputs
- Summary
dslim/bert-base-NER on SageMaker. F1 91.3 on CoNLL-2003. Extracts PER, ORG, LOC, MISC entities in your own VPC -- no data leaving your account, flat $0.08/hr.
- Input MIME type
- application/json
https://waltsoft-marketplace-assets.s3.amazonaws.com/ml-validation/text-sample/sample.jsonl
https://waltsoft-marketplace-assets.s3.amazonaws.com/ml-validation/text-sample/sample.jsonl
Support
Vendor support
Contact support@waltsoft.net for deployment assistance.
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.
Similar products
Identify mental-health entities,assign assertion status and establish relations between the extracted entities
This solution helps in processing textual data to identify named entities present in the corpus of text.
Transformer NER for English with 18 default entity types and custom types at inference. Runs on CPU; uses a GPU automatically when you deploy on a GPU instance.
Open-source NER model for gene entities in biomedical and clinical text. Trained on BC2GM and optimized for state-of-the-art precision, it enables reliable extraction with fast, easy deployment via Hugging Face Transformers.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.