Word Knowledge Curation Using Clarifying Token Interpretation
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Solution Overview
Problem
Existing data processing systems struggle to effectively generate and utilize knowledge from large volumes of data due to issues such as data accuracy, language ambiguities, and variations in text interpretation, leading to inefficiencies in producing useful information.
Innovation Solution
A computing system that includes AI servers to ingest content, extract knowledge, and interact with user devices to facilitate the generation and utilization of knowledge, utilizing modules like collections, identigen intelligence, and query modules to interpret queries and gather content, ensuring quality thresholds are met before providing responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pattern recognition techniques and statistical reasoning are used to process text, then language ambiguities can be addressed, but data accuracy and interpretation consistency deteriorate due to variations in how text is interpreted across languages and dialects
Solution Approach 1:
The patent introduces an intermediary layer between raw text data and knowledge extraction that standardizes interpretation across different languages and dialects. This intermediary processing layer translates varied text interpretations into consistent structured data, resolving the contradiction between handling language diversity and maintaining data accuracy.
2Quantity of substance
If large volumes of data are processed to generate knowledge, then information quantity increases, but useful information production decreases due to difficulties in extracting meaningful patterns from vast data sets
Solution Approach 1:
The patent applies extraction techniques to isolate and remove irrelevant data from large volumes, keeping only the essential knowledge elements. By extracting only the meaningful patterns and discarding redundant information, the system maintains high productivity while processing extensive data sets.
Solution Approach 2:
The patent segments large volumes of data into manageable units or chunks that can be processed efficiently. By dividing the data processing task into smaller segments, the system can extract useful information more effectively without being overwhelmed by the total data volume, thus improving productivity.
3Manufacturing precision
If grammar based techniques force words to support grammatical operations, then sentence construction accuracy improves, but word meaning interpretation deteriorates because the actual descriptive intent of words is not identified
Solution Approach 1:
The patent employs dynamic processing that adapts grammatical analysis to the specific context of each word. Rather than forcing rigid grammatical structures, the system dynamically adjusts interpretation based on contextual cues, preserving both sentence construction accuracy and word meaning interpretation by allowing flexibility in the analysis process.
Data Source
AI summary
A method executed by a computing device includes determining a symbolic representation of words to produce tokens and generating a first equation package for the tokens that corresponds to a first permutation of interpretation of the tokens based on one or more different meanings of the symbolic representations to produce interim knowledge. The method further includes updating the first equation package that optimizes an interpretation confidence level for the tokens based on clarifying tokens—to produce a second equation package that includes a sequence of second selected equation elements that corresponds to a second permutation of interpretation of the tokens as updated interim knowledge. The method further includes establishing a single sequence of selected equation elements as curated knowledge representing the words when the updated interim knowledge contains a single sequence of selected equation elements that corresponds to a permutation of interpretation of the of tokens.