Language Model Form Extraction for Structure-Preserving Data Models
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Solution Overview
Problem
Rendering forms into computer-usable data models is challenging due to the difficulty in capturing form structure and transforming raw text into a specific data structure without a summary, which complicates working with the text.
Innovation Solution
A method and system that utilize a data extraction controller to extract text from a raw data structure, determine text types, generate prompts for a language model to request enhanced information, and apply a data model generator to define a computer-readable representation of the form using a combination of text and enhanced information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If screen scraping application is used to extract text from form, then text extraction is achieved, but form structure and placement information are not captured
Solution Approach 1:
The patent segments the form processing into distinct components: text extraction, structure detection, and data model generation. By dividing the raw form data into separable elements (text content, structural relationships, placement information), the system can process and preserve each aspect independently, thereby capturing complete form structure information while maintaining operational simplicity.
2Ease of manufacture
If raw text is obtained from form, then text extraction is complete, but transformation into specific data structure becomes difficult
Solution Approach 1:
The patent applies preliminary action by detecting and preserving form structure and placement information before the text transformation process. The system pre-processes the form to identify structural relationships and spatial arrangements, then incorporates this information into the data model generation stage, making the subsequent transformation into specific data structures significantly easier.
Solution Approach 2:
The patent introduces an intermediary data model that serves as a bridge between raw text extraction and final data structure transformation. This intermediate representation captures both text content and structural information in a standardized format, facilitating easier transformation into target data structures while preserving all necessary contextual information.
3Ease of operation
If no summary of form is available, then processing speed is maintained, but difficulty of working with raw text increases
Solution Approach 1:
The patent extracts and separates summary information from the complete form processing pipeline. By generating summaries as a distinct, optional component that can be independently controlled, the system provides ease of operation when summaries are needed while allowing processing to proceed at full speed when summaries are not required, thus resolving the time-ease contradiction.
Data Source
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AI summary
One or more embodiments provide for a method. The method includes applying, to a raw data structure defining a form, a data extraction controller to extract text from the raw data structure. The method also includes determining a text type of the text. The method also includes generating, according to the text type, a prompt for a language model to request enhanced information. The enhanced information includes information implicit in the form. The method also includes applying, with the prompt, the language model to the text to generate the enhanced information. The method also includes applying a data model generator to define a data model with a combination of the text and the enhanced information. The data model is a computer-readable representation of the form.