Clause-Based Question Detection in Natural Language Processing
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Solution Overview
Problem
Conventional automated question detection methods are error-prone and computationally expensive, making them unsuitable for real-time and low-power applications, as they treat each sentence as a whole and rely on n-grams or hierarchical trees, which fail to account for intervening words and are resource-intensive.
Innovation Solution
The approach breaks down sentences into clauses and applies question detection rules that define orders of parts of speech, allowing for intervening words and improving flexibility, using a system that separates sentences into clauses and applies rules to identify questions based on wh-words, modal or auxiliary verbs, and BE/HAVE words.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional approaches treat each sentence as a whole using n-grams or hierarchical trees, then question detection can be performed, but the approach becomes computationally expensive and resource heavy
Solution Approach 1:
The patent segments sentences into clauses and further into phrases, applying question detection rules to smaller linguistic units rather than processing entire sentences at once. This segmentation reduces computational complexity and resource consumption while maintaining detection accuracy.
Solution Approach 2:
The patent applies partial action by using simplified question detection rules that only examine specific patterns (wh-words followed by modal verbs or BE/HAVE words) rather than performing complete syntactic analysis. This partial approach reduces computational overhead while sufficient for the detection task.
2Measurement precision
If n-gram approach is used to detect questions, then keyword matching is simple, but it cannot account for intervening words or words located in the middle of the sentence
Solution Approach 1:
The patent introduces dynamic detection rules that can adapt to different sentence structures. The rules flexibly match patterns where wh-words are followed by modal verbs or BE/HAVE words, allowing intervening words to be present. This dynamic approach increases accuracy without requiring complex fixed n-gram configurations.
Solution Approach 2:
The patent changes the detection parameters from fixed n-gram sizes to flexible pattern-matching rules that accommodate variable word sequences. The rules specify relationships between word types (wh-words, modal verbs, BE/HAVE words) rather than fixed positional n-grams, enabling accurate detection despite intervening words.
3Measurement precision
If hierarchical tree parsing is used to analyze sentence structure, then syntactic structure can be produced, but the approach becomes computationally expensive and slow
Solution Approach 1:
The patent extracts only the essential information needed for question detection from the sentence structure, rather than performing complete hierarchical parsing. By focusing on identifying wh-words, modal verbs, and BE/HAVE words in specific sequences, the system obtains sufficient syntactic information without the computational overhead of full tree parsing.
Solution Approach 2:
The patent uses simple, lightweight detection rules that can be quickly applied to each clause without requiring complex parsing infrastructure. These disposable-like rules are computationally inexpensive and can be rapidly executed, providing fast processing speeds while maintaining adequate accuracy for the detection task.
Data Source
AI summary
Systems and methods may provide for separating a sentence into a plurality of clauses and applying a set of question detection rules to each of the plurality of clauses. Additionally, the sentence may be automatically designated as a question if the question detection rules indicate that at least one of the plurality of clauses is a question. In one example, at least one of the question detection rules defines an order of a plurality of parts of speech.