Conditional Clause Role Tagging for Accurate NLP Parsing
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Solution Overview
Problem
Traditional natural language processing systems struggle to accurately identify and interpret conditional clauses in sentences due to their diverse forms and complex relationships with other sentence parts, leading to inaccuracies in parsing and understanding.
Innovation Solution
A computer-implemented method using a natural language processor with a set of rules to determine conditional clauses, leveraging syntactic and semantic information, and an aligner to refine the identification of these clauses and their relationships with other sentence parts, along with a rule executor to perform trigger activities and resolve conflicts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional parsers use simplistic analysis to process sentences, then processing speed is maintained, but accuracy in identifying conditional clauses and their relationships deteriorates
Solution Approach 1:
The system segments the sentence processing task into distinct components: conditional clause identification, relationship determination, and role assignment. By dividing the complex parsing task into manageable segments handled by specialized modules, the system achieves higher accuracy in identifying conditional clauses without requiring a complete overhaul of the entire parsing system.
Solution Approach 2:
The patent introduces intermediary components such as conditional clause identifiers and relationship determiners that act as mediators between the input sentence and the final parsed output. These intermediaries specialize in handling the complex logic of conditional clauses, allowing the main parser to operate with simpler rules while maintaining high overall accuracy.
2Reliability
If traditional parsers use simplistic analysis, then system complexity is reduced, but the ability to properly identify relationships between conditional clauses and other sentence parts deteriorates
Solution Approach 1:
The system applies local quality by implementing specialized processing rules specifically for conditional clauses rather than applying uniform simplistic rules to all sentence structures. The relationship determination module uses targeted logical connection rules that are locally optimized for conditional constructions, improving reliability for this specific clause type without unnecessarily complicating the entire system.
Solution Approach 2:
The patent changes parameters by introducing multiple levels of analysis (identification, relationship determination, role assignment) with varying degrees of complexity applied to different aspects of sentence processing. This allows the system to adjust the complexity parameter locally for conditional clauses while maintaining simpler processing for other sentence elements.
Data Source
AI summary
A natural language processor and applicable method receives an input sentence of natural language from a natural language corpus. The input sentence comprises sentence clauses that include a conditional clause. The processor performs natural language processing (NLP), using an NLP model, on the input sentence. The processing comprises using a set of rules determining the sentence clauses and which of the sentence clause is the conditional clause, determining one or more logical connections between the sentence clauses, and determining a role of the sentence clauses based upon the one or more identified logical connections. The sentence clauses are tagged to produce a labeled sentence that is output to an entity that is one or more of a storage device, a network interface, a storage device, and an input of a further language processor or application.