
Overview
A part of Wipro HOLMES™ E-KYC product, IEF Controller Extractor helps you to identify controllers (CEO, CTO, Chairman etc.) of an organization using the annual report of the organization. Currently annual reports of only '.pdf' form are supported. It is recommended that the model be used in batch transform mode wherein you can keep a base64 encoded file as part of the input schema in s3 bucket. Sample code on converting a file to Base64 string can be found in additional resources. Currently the model supports documents from Australia (AUS) & Canada (CAN) geographies.
Highlights
- Now you can use Wipro HOLMES™ IEF Controller Extractor module to extract controllers of an organization. This model can be used directly inside your own products to extract and provide information about an organization.
Details
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Pricing
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.00 |
ml.m5.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.2xlarge instance type, real-time mode | $0.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $0.00 |
Vendor refund policy
Since you are not being charged currently for the use of this software there will be no refund of any charges.
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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.
Version release notes
This is the first version of the model
Additional details
Inputs
- Summary
Requirements for consuming the service: a. Subscription access to Amazon Sage maker and the model product. b. S3 bucket for specifying input and output locations. c. Necessary permissions to S3 locations and model packages. d. Code scripts for encoding/decoding files to/from base64 format for use in consumer scripts.
Input schema: To use the model create a batch transform job and place your input data in the following schema in a json file in your input s3 bucket: { "geo" : "AUS", "org" : "ABC Limited", "threshold" : "0.8", "file" : "sbfuf()&%#=dhbsdb++fb*++" } geo: The geographical location. Currently Australia (AUS) & Canada (CAN) are supported geographies. org: Name of the organization. threshold: Threshold of the confidence score file: Base64 encoded pdf file
Output schema: Batch transform job will create an output file of extension ‘.out’ in the output s3 bucket specified by user in the request. The schema of output is described below. { "status":"success", "output":[ { "text":{ "File":"ABC Limited", "Sentence":"Yours sincerely Mr Xyz Chairman." }, "classes":[ "BOARD_MEMBER_DESG" ], "confidence":[ "0.96" ], "entity1":{ "entity_name":"Mr Xyz", "entity_nerclass":"PERSON" }, "entity2":{ "entity_name":"Chairman", "entity_nerclass":"DESG" } }, { "text":{ "File":"ABC Limited", "Sentence":"In April 2014, Mr ABC was appointed Chief Executive Officer and has continued to play an instrumental role in driving and delivering key innovation and successes for the Group." }, "classes":[ "BOARD_MEMBER_DESG" ], "confidence":[ "0.99" ], "entity1":{ "entity_name":"Mr ABC", "entity_nerclass":"PERSON" }, "entity2":{ "entity_name":"Chief Executive Officer", "entity_nerclass":"DESG" } } ] }
status: Whether the request completed successfully. text: The details of inference i.e. which text in the file was used for designation extraction. a. File: Name of the organization b. Sentence: The sentence identified for information extraction.
class: Class of extracted relation. This is internal to IEF and may not be useful for the user. confidence: The confidence score of the extracted controller of organization. entity1 & entity2: a. entity_name: Name of the entity extracted from text. b. entity_nerclass: NER tag of the entity.
- Input MIME type
- application/json
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