Sentence Pattern Decomposition for Foreign Phrase Learning
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Solution Overview
Problem
Existing technologies struggle to accurately identify and decompose compound sentences in foreign languages into basic sentences, determine sentence patterns, and update tree information to learn foreign language phrases, especially when dealing with morpheme-based or word-based languages with varying grammars.
Innovation Solution
A foreign language phrases learning system that decomposes compound sentences into basic sentences, identifies sentence patterns based on word segments, and updates tree information using additional information extraction and storage in morpheme or word dictionaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If compound sentences are decomposed into basic sentences and tree information is updated, then foreign language phrase understanding accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments compound sentences into basic sentences by identifying sentence boundaries and structural components. This decomposition allows the system to analyze and understand foreign language phrases by breaking down complex sentences into manageable units, thereby improving understanding accuracy while managing system complexity through structured processing.
Solution Approach 2:
The system introduces a hierarchical dimension by creating tree structures that represent sentence components and their relationships. This dimensional transformation from linear text to hierarchical tree structures enables comprehensive phrase understanding while organizing complexity in a manageable framework through multiple levels of linguistic analysis.
2Adaptability or versatility
If sentence patterns are determined based on word segments and additional information is extracted, then language analysis capability is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-identifying sentence patterns and extracting additional information during the decomposition phase. By preparing and organizing linguistic data structures in advance, the system enhances language analysis capability while reducing the time required for subsequent processing and interpretation stages.
3Manufacturing precision
If morpheme-based or word-based sentence decomposition is performed, then grammatical accuracy is improved, but computational complexity increases
Solution Approach 1:
The system applies local quality by adapting the decomposition approach to the specific characteristics of each foreign language. By identifying whether a language is morpheme-based or word-based and applying the appropriate decomposition method, the system achieves high grammatical accuracy for each language type while managing computational complexity through targeted, language-specific processing strategies.
Data Source
AI summary
Disclosed is a foreign language phrases learning system based on basic sentence pattern unit decomposition, and implemented in a computing device including at least one processor and at least one memory for storing instructions executable by the processor, which includes: a sentence decomposition unit, when a natural language composed of a foreign language is input from a user, for decomposing a compound sentence corresponding to the input natural language into a plurality of basic sentences; a sentence pattern determination unit for checking one of morphemes or words contained in each of the decomposed basic sentences when the compound sentence is completely decomposed by the sentence decomposition unit, thereby determining a sentence pattern for each of the basic sentences; an additional information designation unit, when the sentence pattern for each of the basic sentences is completely determined by the sentence pattern determination unit, for designating some of the morphemes or the words contained in each of the basic sentences as additional information; and an additional information storage unit for matching the additional information with one of the morphemes or the words, which are not designated as the additional information, when the designation of the additional information is completed, thereby storing the additional information in a basic morpheme category included in a pre-stored basic morpheme dictionary table. In addition, various embodiments identified through the present document are possible.