Complex Predicate Template Collecting Apparatus for Social Scenario Prediction
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Solution Overview
Problem
Current question-answering systems cannot predict future events considering every risk and chance, limiting their ability to provide information useful for decision-making in complex scenarios like social movements or global influences.
Innovation Solution
A complex predicate template collecting apparatus that extracts and calculates polarities from natural language sentences to generate social scenarios by combining simple and complex predicate templates, including sahen-nouns, trouble-nouns, and quantifier nouns, to predict future events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional question-answering systems are used, then they can provide accurate answers to factual questions, but they cannot predict future events or provide information useful for decision-making in complex scenarios
Solution Approach 1:
The system segments the complex task of future prediction into multiple components: extracting simple predicate templates from documents, combining them into complex predicate templates, determining polarities of nouns, and calculating overall template polarities. This segmentation allows each component to be processed separately and reliably, while collectively achieving future event prediction capability
Solution Approach 2:
The system performs preliminary actions by pre-extracting and storing simple predicate templates from documents before prediction tasks. These templates are prepared in advance with their polarities determined, so that when prediction is needed, the system can quickly combine them into complex templates and calculate results without starting from scratch
2Loss of information
If the system extracts and processes information from a huge amount of documents to generate social scenarios, then it can provide comprehensive prediction information, but the complexity of the system increases
Solution Approach 1:
The system performs preliminary information extraction and template creation from documents before actual prediction tasks. Simple predicate templates are extracted and stored in advance, along with their polarities. This preliminary processing reduces the complexity of real-time analysis while ensuring comprehensive information coverage from the document corpus
Solution Approach 2:
The system creates template copies that represent patterns from the original documents. Instead of processing entire documents during prediction, it uses compact predicate template representations that capture the essential information. These templates can be combined and reused multiple times, reducing processing complexity while maintaining information completeness
Data Source
AI summary
A system for collecting elements as a basis for generating a social scenario useful to make a well-balanced good decision. A complex predicate template collecting apparatus includes: a simple predicate template DB storing simple predicate templates having positive or negative polarity values added; an object noun dictionary; a complex predicate template candidate extractor extracting complex predicate template candidates each formed of a combination of a word specified by the object noun dictionary and a simple predicate template, from a WEB archive; a sahen-noun polarity adder, a quantifier noun polarity adder and a trouble-noun polarity adder, determining polarity of a noun in each of the complex predicate template candidate; and a complex predicate template polarity calculator calculating polarity of a complex predicate template candidate by a combination of the polarity of the noun and the polarity of the simple predicate template included in the complex predicate template.