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Transport & Logistics — Taxonomy Extraction and SOP Update Pipeline

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This DAG extracts key information to create and update taxonomies and standard operating procedures (SOPs) using Named Entity Recognition (NER) techniques. It enhances knowledge accessibility within the organization by integrating results into a centralized knowledge portal.

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Overview

The purpose of this DAG is to streamline the extraction and updating of taxonomies and standard operating procedures (SOPs) within the Transport & Logistics industry. It begins by ingesting various data sources, including operational documents, compliance reports, and previous SOPs. The ingestion pipeline utilizes advanced Named Entity Recognition (NER) techniques to identify and classify relevant entities within these documents. The processing steps involve cleaning the data, applying NER algor

The purpose of this DAG is to streamline the extraction and updating of taxonomies and standard operating procedures (SOPs) within the Transport & Logistics industry. It begins by ingesting various data sources, including operational documents, compliance reports, and previous SOPs. The ingestion pipeline utilizes advanced Named Entity Recognition (NER) techniques to identify and classify relevant entities within these documents. The processing steps involve cleaning the data, applying NER algorithms, validating the extracted entities against predefined criteria, and updating the taxonomies accordingly. Quality controls are implemented to ensure accuracy, including automated checks and manual reviews. The final outputs consist of updated taxonomies, revised SOPs, and a comprehensive report of the changes made. Monitoring key performance indicators (KPIs) such as extraction accuracy, processing time, and user engagement with the knowledge portal provides insights into the effectiveness of the DAG. The business value lies in improved knowledge management, enhanced compliance with regulations, and increased operational efficiency, ultimately leading to better decision-making and reduced risks in transport and logistics operations.

Part of the Data & Model Catalog solution for the Transport & Logistics industry.

Use cases

  • Improves operational efficiency through streamlined processes.
  • Reduces risks associated with outdated SOPs.
  • Enhances compliance management and reporting capabilities.
  • Increases accessibility of critical knowledge resources.
  • Supports informed decision-making across the organization.

Technical Specifications

Inputs

  • • Operational documents from logistics operations
  • • Compliance reports from regulatory bodies
  • • Existing SOPs and taxonomies for reference

Outputs

  • • Updated taxonomies for knowledge management
  • • Revised SOPs reflecting current practices
  • • Change report detailing updates and modifications

Processing Steps

  1. 1. Ingest operational documents and compliance reports
  2. 2. Clean and preprocess the ingested data
  3. 3. Apply Named Entity Recognition to identify entities
  4. 4. Validate extracted entities against predefined criteria
  5. 5. Update taxonomies and SOPs based on validated entities
  6. 6. Generate a change report summarizing updates
  7. 7. Publish updated taxonomies and SOPs to the knowledge portal

Additional Information

DAG ID

WK-1291

Last Updated

2025-04-03

Downloads

49

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