Public Sector — Regulatory Knowledge Entity Extraction and Classification

Overview

The purpose of this DAG is to facilitate the extraction of regulatory knowledge from various documents within the public sector, utilizing advanced Named Entity Recognition (NER) techniques. The primary data sources include internal documents such as policy papers, legal texts, and relevant databases that contain regulatory information. The ingestion pipeline begins with the collection of these documents, followed by preprocessing to prepare the data for analysis. The processing steps involve ap

The purpose of this DAG is to facilitate the extraction of regulatory knowledge from various documents within the public sector, utilizing advanced Named Entity Recognition (NER) techniques. The primary data sources include internal documents such as policy papers, legal texts, and relevant databases that contain regulatory information. The ingestion pipeline begins with the collection of these documents, followed by preprocessing to prepare the data for analysis. The processing steps involve applying NER algorithms to identify and extract regulatory terms, which are then classified according to a predefined taxonomy that aligns with public sector compliance requirements. Quality control measures are implemented throughout the process to ensure the accuracy and reliability of the extracted data, including validation checks and cross-referencing with established regulatory standards. The outputs of this DAG include a structured dataset of extracted entities, a classification report, and insights into regulatory compliance trends. Monitoring key performance indicators (KPIs) such as extraction accuracy rates and processing times allows for continuous improvement of the workflow. This DAG delivers significant business value by enhancing regulatory compliance, improving decision-making processes, and enabling public sector organizations to efficiently manage their regulatory knowledge.

Part of the Pricing Optimization solution for the Public Sector industry.

Use cases

• Enhanced compliance with regulatory requirements
• Improved decision-making through accurate data insights
• Increased efficiency in regulatory knowledge management
• Reduction in manual data processing efforts
• Timely identification of regulatory changes and trends