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Patent drawing for Accuracy and providing explainability and transparency for query response using machine learning models
US 12,339,839 B2
Computing US 12,339,839 B2 Not in force

Accuracy and providing explainability and transparency for query response using machine learning models

This is a computer system designed to answer questions posed in everyday language. It works by taking your natural language question, understanding it, and then converting it into a specific command for a database, often a graph database. The system then runs this command to retrieve and present the answer.

Why it matters: The rapid advancements in large language models since 2024 have significantly improved the accuracy and ease of translating natural language into complex database queries, making the core "parsing and translating" step more robust.

Status
Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build
SpecializedLLM integration, graph database, data loaders, UI software.

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