Dialectical Model for Question Answering Systems
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Solution Overview
Problem
Current question answering systems face limitations in providing comprehensive and accurate responses to user queries due to their reliance on single-perspective analysis, which may miss alternative evidence and contradictory information.
Innovation Solution
The implementation of a dialectical model that generates both original and opposing natural language processing (NLP) structures to identify evidence for candidate answers, allowing for a broader search and increased accuracy by considering multiple perspectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single-perspective analysis is used in question answering systems, then the system complexity is reduced and processing speed is improved, but the comprehensiveness and accuracy of answers deteriorate due to missing alternative evidence and contradictory information
Solution Approach 1:
The system segments the analysis process into multiple independent perspectives or viewpoints. Each perspective analyzes the query separately to identify supporting evidence, allowing the system to evaluate multiple angles without requiring a completely separate system for each viewpoint.
Solution Approach 2:
A single question answering system is designed to perform multiple functions by incorporating diverse perspectives within its architecture. The system universally handles different viewpoints, evidence types, and analysis approaches through a unified framework that integrates multiple analytical paths.
2Reliability
If multiple perspectives and opposing queries are generated and evaluated, then the comprehensiveness and reliability of answers are improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-identifying multiple perspectives and potential opposing queries before full evaluation. This allows the system to prepare analysis frameworks in advance, reducing the time required during actual query processing while maintaining comprehensive evaluation.
Solution Approach 2:
The evaluation process maintains continuity by systematically processing multiple perspectives in an integrated workflow rather than discrete, repetitive cycles. This continuous action approach reduces idle time and computational overhead while ensuring thorough evaluation of all viewpoints.
Data Source
AI summary
A method, system or computer usable program product for utilizing a dialectical model for providing an answer to a user query including receiving, by a system, a natural language query from a user; applying, by the system, natural language processing (NLP) to the query to generate a first set of NLP structures; generating, by the system, a contrary set of NLP structures which represent an opposite polarity query to the user query; evaluating, by the system, the first set of NLP structures to identify a first set of evidence for candidate answers; evaluating, by the system, the contrary set of NLP structures to identify a second set of evidence for candidate answers; evaluating, by the system, a first set of hypotheses from the first set of NLP structures based on the first set of evidence for candidate answers, and a contrary set of hypotheses from the contrary set of NLP structures based on the second set of evidence for candidate answers, to determine a set of answers to the user query; converting, by the system, the set of answers to natural language; and providing the converted set of answers to the user.