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Open data
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Deployed on AWS
Name Entity Recognition datasets containing short sentences and queries with low-context,
including LOWNER, MSQ-NER, ORCAS-NER and Gazetteers (1.67 million entities).
This release contains the multilingual versions of the datasets in [Low Context Name Entity Recognition (NER) Datasets with Gazetteer](https://registry.opendata.aws/lowcontext-ner-gaz/).
Overview
Name Entity Recognition datasets containing short sentences and queries with low-context, including LOWNER, MSQ-NER, ORCAS-NER and Gazetteers (1.67 million entities). This release contains the multilingual versions of the datasets in Low Context Name Entity Recognition (NER) Datasets with Gazetteer .
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
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
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- Data file
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::code-mixed-ner
- AWS region
- us-east-1
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://code-mixed-ner/
Resources
Vendor resources
Support
Contact
Managed By
How to cite
Multilingual Name Entity Recognition (NER) Datasets with Gazetteer was accessed on DATE from https://registry.opendata.aws/code-mixed-ner .
License
Similar products
See https://lowcontext-ner-gaz.s3.amazonaws.com/readme.html
This solution helps in processing textual data to identify named entities present in the corpus of text.
Co-innovated with the AWS Generative AI Innovation Center (GenAIIC) Partner Agent Factory (PAF), Crayon refiNER is a multilingual, agentic entity recognition framework that enhances existing NER systems with large language models and adaptive refinement. It acts as an intelligent reflection layer that automatically identifies, validates, and improves entity extraction across different domains and languages. Using contextual reasoning and web-based validation, Crayon refiNER delivers accurate, explainable, and scalable results. Designed for enterprise NLP workflows, it improves precision, reduces manual effort, and continuously adapts to new data and domains without the need for retraining.
Rerank will return a sorted list of documents based on the semantic similarity between the query and documents in over 100 languages.