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Extract text from scanned documents
Query Parser

Query Parser

Extract key entities from text queries

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What is Query Parser ?

Query Parser is a specialized tool designed to extract key entities from text queries, particularly focused on scanned documents. It leverages advanced AI technology to identify and retrieve relevant information, making it easier to process and analyze data from unstructured or semi-structured text sources.

Features

• Entity Extraction: Accurately identifies and extracts key entities such as names, dates, locations, and organizations from text.
• Scanned Document Compatibility: Capable of processing text from scanned documents, including handwritten or OCR-processed text.
• High Accuracy: Utilizes AI models to ensure precise extraction even from low-quality or complex layouts.
• Customizable: Allows users to define specific entities or patterns to extract based on their needs.
• Real-Time Processing: Provides quick results, enabling efficient workflows for users.
• Integration-Friendly: Can be seamlessly integrated into existing systems or workflows.

How to use Query Parser ?

  1. Upload Your Document: Load the scanned document or text file into the tool.
  2. Select Parsing Options: Choose predefined entity types or customize your extraction criteria.
  3. Run the Parser: Initiate the extraction process to analyze the text.
  4. Review Results: Examine the extracted entities and verify their accuracy.
  5. Export Data: Save or export the extracted data for further use.

Frequently Asked Questions

What file formats does Query Parser support?
Query Parser supports a wide range of file formats, including PDF, JPEG, PNG, and TXT.

Can I customize the entities extracted by Query Parser?
Yes, Query Parser allows users to define custom entities or patterns to tailor extraction to their specific needs.

How long does it take to process a document?
Processing time varies depending on the document size and complexity. However, Query Parser is optimized for real-time processing, ensuring quick results even for large files.

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