Procedural Step Detection for Unsupported Claims
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Solution Overview
Problem
Content creators face limitations in making assertions due to their personal knowledge, which can lead to the inclusion of unsupported claims and undesirable procedural steps in texts, such as research papers and clinical trial protocols, potentially resulting in inaccurate or harmful content.
Innovation Solution
A system and method that utilize processors and storage devices to detect procedural steps and claims within texts, automatically search for related steps and outcomes in a corpus of references, and analyze these for detrimental results, providing indicators to users to refine their content and avoid unsupported assertions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If content creators rely on personal knowledge to make assertions, then the content creation process is simple and quick, but the accuracy and supportability of claims is limited
Solution Approach 1:
The patent introduces an intermediary system comprising procedural step detection module, related procedural step extraction module, and outcome extraction module. These modules act as mediators between the content creator and the corpus of references, automatically detecting procedural steps, extracting related steps from references, and identifying outcomes without requiring the content creator to manually review numerous sources. This intermediary system enhances claim accuracy while maintaining simplicity for the user.
Solution Approach 2:
The system enables self-service by automatically performing literature review and outcome assessment functions that would traditionally require manual effort from content creators. The procedural step detection module automatically identifies steps in the text, the related procedural step extraction module autonomously searches the corpus for related steps, and the outcome extraction module automatically determines whether outcomes are detrimental, freeing the content creator from manual research while improving accuracy.
2Reliability
If content creators manually review existing literature to support claims, then the supportability of assertions improves, but the time and effort required increases significantly
Solution Approach 1:
The patent replaces the manual mechanical process of literature review with an automated computational system. Instead of content creators manually searching, reading, and analyzing existing literature, the system uses the related procedural step extraction module to automatically search the corpus, extract relevant procedural steps, and the outcome extraction module to automatically analyze outcomes. This substitution of manual mechanical review with automated processing dramatically reduces time while maintaining or improving supportability of claims.
Solution Approach 2:
The system performs preliminary action by proactively searching for and extracting related procedural steps and outcomes before the content creator finalizes their content. The procedural step detection module identifies steps in advance, the related procedural step extraction module pre-searches the corpus for relevant information, and the outcome extraction module提前 determines potential detrimental outcomes, allowing the content creator to make informed decisions without time-consuming manual review.
3Manufacturing precision
If content creators are familiar with more prior procedures and outcomes, then the quality of new procedures improves, but the capacity to process and retain information becomes a limiting factor
Solution Approach 1:
The patent transitions from a one-dimensional limitation of human information processing capacity to a multi-dimensional solution by leveraging the computational dimensions of automated text analysis. The system processes information across multiple dimensions simultaneously: the procedural step detection module analyzes text structure, the related procedural step extraction module searches the corpus across multiple sources, and the outcome extraction module evaluates multiple outcomes in parallel. This dimensional expansion allows the system to process and retain far more information than a single content creator could handle, thereby improving procedure quality without being constrained by human information processing limits.
Data Source
AI summary
Procedural optimization is facilitated by receiving user input for creating or modifying a body of text comprising a procedure, detecting one or more procedural steps associated with the procedure using a procedural step detection module, automatically searching within a corpus of references for one or more related procedural steps using a related procedural step extraction module, automatically identifying one or more outcomes within the corpus of references associated with the one or more related procedural steps using an outcome extraction module, automatically determining whether the one or more outcomes comprise detrimental results using an outcome analysis module, and, in response to determining a set of detrimental outcomes from the one or more outcomes that comprise detrimental results, presenting a detriment indicator within the user interface in association with the one or more procedural steps.