High Tech — Entity Extraction and Taxonomy Construction Pipeline

Overview

The primary purpose of this DAG is to extract key entities from diverse data sources and build a structured taxonomy to facilitate efficient search and retrieval in high-tech environments. The data sources include unstructured text documents, product specifications, and customer feedback, which are ingested through a robust data pipeline. The ingestion process starts with data collection, followed by normalization and preprocessing to ensure consistency. The core processing steps involve Named E

The primary purpose of this DAG is to extract key entities from diverse data sources and build a structured taxonomy to facilitate efficient search and retrieval in high-tech environments. The data sources include unstructured text documents, product specifications, and customer feedback, which are ingested through a robust data pipeline. The ingestion process starts with data collection, followed by normalization and preprocessing to ensure consistency. The core processing steps involve Named Entity Recognition (NER) to identify relevant entities, followed by hybrid indexing techniques to enhance search relevance. Quality control measures are implemented, where subject matter experts validate extracted entities to ensure accuracy and reliability. The outputs of this DAG include a comprehensive taxonomy accessible through business portals, along with enriched datasets for further analysis. Monitoring key performance indicators (KPIs) such as the accuracy rate of extracted entities and query response times is crucial for assessing the effectiveness of the pipeline. The business value lies in improved search efficiency, enhanced user experience, and better decision-making capabilities driven by accurate and relevant data.

Part of the Knowledge Portal & Ontologies solution for the High Tech industry.

Use cases

• Increased accuracy in entity identification and classification
• Faster search results leading to improved productivity
• Enhanced user experience through relevant data access
• Better decision-making supported by reliable information
• Scalable solution adaptable to evolving data needs