Sold by: MphasisÂ
Deployed on AWS
This solution helps in processing textual data to identify geopolitical entities present in the corpus of text.
Overview
Mphasis DeepInsights Geopolitical Entity Recognizer is an efficient way of identifying geopolitical entities present in the corpus of text. This solution applies NLP techniques to extract the geopolitical entities which can be used for providing useful insights about the text and further text analytics. The model takes a corpus of text as input file, processes it and provides a csv file containing all the geopolitical entities present in the text as output.
Highlights
- Mphasis DeepInsights Geopolitical Entity Recognizer is a Natural Language Processing based solution for extracting geopolitical entities such as countries, cities and states present in the text data.
- The model can take a maximum of 350kb ( ~ 2500 rows of text) as input and extract geopolitical entities present in the text.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need Customized Deep learning and Machine Learning Solutions? Get in Touch!
Details
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Delivery method
Latest version
Deployed on AWS
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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.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $8.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $4.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $8.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $8.00 |
ml.m5.12xlarge Inference (Batch) | Model inference on the ml.m5.12xlarge instance type, batch mode | $8.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $8.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $8.00 |
ml.c4.4xlarge Inference (Batch) | Model inference on the ml.c4.4xlarge instance type, batch mode | $8.00 |
ml.m5.xlarge Inference (Batch) | Model inference on the ml.m5.xlarge instance type, batch mode | $8.00 |
ml.c5.9xlarge Inference (Batch) | Model inference on the ml.c5.9xlarge instance type, batch mode | $8.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
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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
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
- Supported content types: text/csv.
- The input has to be a '.txt' file with 'utf-8' encoding.
- Limitations for input type
- Maximum input file size: 350kb ( ~ 2500 rows of text).
- Input MIME type
- text/csv, text/plain
https://github.com/Mphasis-ML-Marketplace/Geopolitical-Entity-Recognizer/tree/main/Input
https://github.com/Mphasis-ML-Marketplace/Geopolitical-Entity-Recognizer/tree/main/Input
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
Input.txt | Input is a text file from which geopolitical entities needs to be extracted. | Type: FreeText | Yes |
Resources
Vendor resources
Support
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