Patent Document Annotation via LLM API Mediation
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Solution Overview
Problem
The integration and operation of large language models (LLM) for natural language processing are costly and complex, making it difficult for organizations to incorporate them into their systems, necessitating reliance on external services.
Innovation Solution
A data processing system comprising components that utilize a large language model to extract and annotate special technical features from patent documents, create summaries, and generate claim drafts, while providing user-friendly interfaces for input and display of annotated documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large language model is integrated into an organization's system, then the capability of natural language processing is significantly increased, but the facility requirements and costs increase
Solution Approach 1:
The patent uses an intermediary service provider that hosts the large language model and provides API access. This mediator allows organizations to access advanced NLP capabilities without integrating the complex model infrastructure themselves, resolving the contradiction between enhanced capability and reduced facility requirements
Solution Approach 2:
Instead of copying the entire large language model infrastructure, the patent uses API interfaces that replicate the functionality of the model through remote procedure calls. This allows organizations to access model capabilities without acquiring the underlying computational resources
2Adaptability or versatility
If a large language model is integrated into an organization's system, then the capability of natural language processing is significantly increased, but the costs increase
Solution Approach 1:
The service provider acts as an intermediary that manages the costs of running large language models. Organizations pay for NLP capabilities through API calls rather than bearing the full cost of model training and inference infrastructure, converting fixed capital expenses into variable operational expenses
Solution Approach 2:
Instead of investing in expensive, long-term model infrastructure, the patent enables organizations to access NLP capabilities through pay-per-use API calls. This transforms the cost structure from high upfront investment to lower, more flexible operational costs
3Device complexity
If external services are used for large language models, then the facility and cost complexity is reduced, but the integration and operation becomes more difficult
Solution Approach 1:
The patent creates a universal interface layer that handles multiple NLP tasks through a single API system. This multi-functional approach simplifies integration by providing a consistent interface for various language processing operations rather than requiring separate integrations for different functions
Solution Approach 2:
The system incorporates feedback mechanisms where the service provider receives usage patterns and performance data from integrating organizations, allowing continuous optimization of the API interface and response formats. This feedback loop reduces integration difficulty over time by adapting to common usage patterns
Data Source
AI summary
A novel data processing system that is highly convenient, useful, or reliable is provided. The data processing system is composed of three components. A component 1 receives identification data, transmits the identification data to a component 3, and provides an annotated document. A component 2 extracts a special technical feature and generates the annotated document with the use of a large language model. The component 3 receives and shares the identification data and the special technical feature, and creates and shares a table. The component 3 includes two subcomponents. A subcomponent 1 manages a patent application document and an examination record with the use of a database and a management system. A subcomponent 2 creates a prompt to extract the special technical feature and generate the annotated document.