Textual Narrative Quality Analysis Using NLP

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Solution Overview

Problem

Corporations and organizations face challenges in assessing the quality of textual narratives, leading to inefficiencies and resource wastage due to poor quality or duplicate narratives, which can result in miscommunication and unnecessary changes in product development.

Innovation Solution

A method and system for analyzing textual narratives using Natural Language Processing (NLP) techniques to compare them against quality criteria such as syntactical, semantic, and pragmatic requirements, providing feedback on quality and suggesting improvements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual review of textual narratives is performed, then quality assessment accuracy is improved, but time consumption and resource usage increase

Engineering Contradiction:

Improvequality assessment accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical review processes with an automated computational system that uses natural language processing and quality criterion algorithms to assess textual narratives, thereby eliminating time-consuming human review while maintaining assessment accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables textual narratives to be automatically evaluated against predefined quality criteria without requiring external human intervention, allowing the narratives to 'self-assess' their quality through computational comparison with established standards

Inventive Principle:

Principle #25Self-service

2Productivity

If no quality checking mechanism is implemented, then productivity is improved, but resource wastage increases due to duplicate or poor quality narratives

Engineering Contradiction:

ImproveproductivityVSAvoidresource wastage

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The patent implements quality checking as a preliminary step before textual narratives are processed further or stored, preventing duplicate or poor quality narratives from entering the system and causing resource wastage later in the workflow

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides automated feedback on narrative quality by comparing submitted narratives against predefined quality criteria and identifying issues such as duplication, ambiguity, or incompleteness, enabling immediate correction before resources are wasted

Inventive Principle:

Principle #23Feedback

3Reliability

If comprehensive quality criteria are applied, then narrative quality is improved, but system complexity increases

Engineering Contradiction:

Improvenarrative qualityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent divides comprehensive quality assessment into distinct, modular quality criteria (e.g., clarity, completeness, consistency, duplication check) that can be independently evaluated and combined, making the complex assessment process manageable and systematic

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system uses a universal set of quality criteria that can be applied to any textual narrative regardless of domain or purpose, allowing a single multi-functional system to handle diverse quality assessment needs without requiring separate specialized systems

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Speed

If automated analysis is implemented, then processing speed is improved, but measurement precision may deteriorate

Engineering Contradiction:

Improveprocessing speedVSAvoidquality assessment accuracy

Core Design Contradiction:

SpeedVSMeasurement precision

Solution Approach 1:

The patent replaces human manual review with automated natural language processing systems that can analyze narratives at high speed while maintaining consistent application of quality criteria, eliminating human variability and fatigue that can affect assessment accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12299396B2Method and system for analyzing textual narratives using quality criteria

Publication Date: 2025.05.13 JPMORGAN CHASE BANK NA

AI summary

A system and method for analyzing a textual narrative are provided. The method includes: receiving, from a user, an input that includes a textual narrative; comparing the textual narrative to various types of quality criteria, including syntactical criteria, semantic criteria, and pragmatic criteria; determining, based on the comparison, whether the textual narrative satisfies the quality criteria; and providing an output that indicates a result of the determination. The textual narrative may be a JIRA user story or a JIRA epic. The comparison may be performed by using one or more Natural Language Processing techniques.