Unstructured Data Extraction via Dynamic Template Rules
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Solution Overview
Problem
Manual review of unstructured data for claim processing is time-consuming and expensive due to the lack of semantic context in existing data extraction methods, which often rely on hardcoded and non-transparent algorithms, limiting flexibility and transparency.
Innovation Solution
A system and method for generating a structured report from unstructured data using customizable template rules, where predefined templates define extraction rules for identifying relevant data, allowing users to refine and modify these rules dynamically to improve data extraction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of unstructured data is performed, then data extraction can be done, but the process is time-consuming and expensive
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated computer-based system that uses extraction rules and templates to identify and extract relevant data from unstructured documents, eliminating the need for human reviewers to manually parse through documents
Solution Approach 2:
The system enables self-service data extraction by allowing users to define their own extraction rules and templates, making the system adaptable to different data extraction needs without requiring manual reconfiguration or expert intervention for each new extraction task
2Productivity
If hardcoded extraction algorithms are used, then data extraction can be automated, but the system lacks flexibility and transparency
Solution Approach 1:
The patent implements dynamic extraction rules that can be modified and adjusted by users based on changing requirements. The system allows rules to be updated without reprogramming, enabling adaptive extraction across different document types and data requirements while maintaining automation
Solution Approach 2:
The system incorporates feedback mechanisms where extraction results can be reviewed and used to refine extraction rules. This allows the system to learn from actual extraction outcomes and improve its performance over time while maintaining transparency in the extraction process
3Measurement precision
If sophisticated data extraction methods are used, then extraction capability is improved, but the system becomes a black box without transparency
Solution Approach 1:
The patent segments the extraction process into distinct, understandable components including templates, extraction rules, and data fields. This segmentation makes the extraction process transparent and interpretable while maintaining high extraction accuracy through structured rule application
Data Source
AI summary
Methods and systems for providing computer-assisted guided review of unstructured data to generate a structured data output based on customizable template rules. In embodiments, an unstructured file is received, and a predefined template is selected. The predefined template includes a plurality of fields, each field corresponding to a field of the structured report. The predefined template also defines extraction rules for each field of the predefined template, and the extraction rules define parameters for identifying unstructured data relevant to the associated field. The extraction rules are applied to the unstructured file to identify data relevant to the field associated with the corresponding extraction rule, and the data identified as relevant is confirmed. Confirming the relevant data includes determining to refine the relevant data based on a condition, and modifying the extraction rule associated with the field to refine the relevant data.