Polysemy Disambiguation in Machine Translation via Contextual Related Words
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing translation technologies face low accuracy when translating polysemous words due to their multiple meanings, leading to errors in translation processes.
Innovation Solution
A method and apparatus that identify polysemous words in source language text, inquire related words corresponding to each interpretation, determine a target interpretation based on context, and translate the polysemy into the appropriate meaning, utilizing a polysemy library and corpus analysis to ensure accurate translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If translation machines use standard translation algorithms to translate polysemous words, then translation speed is improved, but translation accuracy deteriorates due to multiple meanings causing errors
Solution Approach 1:
The system performs preliminary action by building a polysemy library that pre-stores multiple interpretations and related words for polysemous vocabularies before the actual translation process. When translating, the system queries this pre-built library to quickly retrieve candidate meanings and their associated related words, enabling fast disambiguation without sacrificing accuracy.
Solution Approach 2:
The system introduces an intermediary mechanism - a polysemy library containing related words for each interpretation - that mediates between the source text and target translation. By querying related words from this intermediary library, the system determines the correct interpretation of polysemous words, thereby improving translation accuracy while maintaining efficiency through pre-organized data structures.
2Manufacturing precision
If translators manually translate polysemous words to ensure accuracy, then translation accuracy is improved, but translation efficiency deteriorates due to time-consuming processes
Solution Approach 1:
The system implements self-service by automatically querying the polysemy library and determining the correct interpretation of polysemous words without requiring manual translator intervention. The machine independently analyzes related words, determines target interpretations, and completes translations autonomously, thereby maintaining high accuracy while dramatically improving translation efficiency.
Solution Approach 2:
The system uses feedback mechanisms by analyzing the presence or absence of related words in the source text to determine the correct interpretation of polysemous words. The translation system queries the polysemy library, receives feedback about which related words are present in the context, and uses this feedback to select the appropriate target interpretation, ensuring accuracy without manual intervention.
Data Source
AI summary
Embodiments of the present disclosure provide a method and an apparatus for translating a polysemy, and a medium. The method includes: obtaining a source language text; identifying and obtaining the polysemy from the source language text; inquiring related words corresponding to each interpretation of the polysemy; determining a target interpretation corresponding to the related words contained in the source language text; and translating the polysemy into the target interpretation.