Automated System for Drafting Patent Claims and Specifications

Automating the generation of patent specifications from claims that are prepared by humans.

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A method for generating patent applications using a dynamic user interface and natural language processing. The user interface features fillable objects where users can drop phrases from claims. These phrases are analyzed to determine their type (e.g., adjective or verb phrase) and context. The system converts these phrases into sentences with proper subjects and context. Additionally, the phrases can be matched with related descriptions in drawings or other documents to enhance accuracy. This approach streamlines the process of creating patent applications by converting claim phrases into coherent and contextually accurate content.

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Generating accurate text for patent applications by combining natural language processing (NLP) with structured templating. The system uses natural language understanding (NLU) to parse input text and extract structured components. It then employs natural language generation (NLG) to produce precise output text using a templating language enhanced with functions to manipulate text based on the data model. This method allows the system to generate sections of patent applications by extracting claim structures from existing applications and inserting the parts into a claim model data object, ensuring accurate and contextually relevant content.

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Automated document creator system that automatically creates templates for patent applications based on identified prior art references. The system automatically creates a template for a drafter based on a record of invention form filled out by the inventor, practitioner, or a combination of the two and at least one piece of prior art identified in a search report.

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Generating patent applications using natural language processing (NLP) and a dynamic user interface that allows users to rearrange and supplement the output from NLP to improve the quality of the generated patent documents. The system uses NLP to analyze the claims and generate a draft patent application. However, the NLP alone may not produce optimal results due to limitations in understanding the claims' formal structure and disambiguating conditions in actions. The user interface allows the user to reorder and add text to the generated application to address these limitations.

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A tool to assist in reading patent documents more accurately, quickly, and comfortably by automatically obtaining and displaying relevant guidance content for drawings, claim elements, and other components of the patent. It displays the illustration data like drawings with element numbers alongside the corresponding guidance targets like claim elements or descriptions. The tool uses algorithms to link the illustration data to specific guidance content sections like claim text or descriptions.

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A patent preparation system that captures important information about the relationship among claim limitations to improve patent drafting efficiency. The system allows users to indicate when a dependent claim corresponds to a specific limitation of an independent claim, rather than the entire claim. It stores this relationship data and generates patent application text that reflects the claim structure. This way, claims, drawings, and specifications can be automatically generated and modified with proper claim dependencies to speed up and improve patent preparation.

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Computer-based patent preparation that facilitates efficient preparation of patent documents. The preparation includes identifying a set of invention features, generating a first tree structure, identifying a second tree structure, and automatically generating one or more patent application documents based at least in part on the first tree structure and the second tree structure.

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Automatically creating patent applications using AI that follows a document plan inferred from example patents. The system analyzes existing patents to identify common formatting features and alignment between claims and specifications. When a new set of claims is received, it uses natural language generation to create a patent application consistent with the learned document plan and claims structure. This aims to produce applications that closely match the format and organization of typical patents.

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System for enhancing computer-generated patent applications by providing non-explicit support for individual claim features to make them more robust and comprehensive. It does this by using machine learning to identify and extract explicit and non-explicit support from the patent specifications for aligning to the claims. It then uses this extracted data to train a model that can generate new non-explicit support statements for previously unseen claim features. The generated support statements can be inserted into draft patent applications to improve their quality and completeness.

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Generating a quality patent application that minimizes associated costs, and more affordable than the current state of the art by producing more patent applications in a lesser amount of time, while still upholding the standards of quality and integrity. The generation includes receiving information relevant to drafting a document, receiving guidelines and standards of patentability, analyzing the received information, determining the patentability of the invention, based on the analyzed received information, and generating the document for the invention, based on a learned behavior.

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Computer method for automatically acquiring and correlating reference numerals of element-nouns in patent claims, specifications, and drawings. The method involves searching the specification to find specification-element-noun reference numerals and connecting them to claim-element-nouns. It also maps drawing-nouns to the correlated specification-element-nouns and claim-element-noun reference numerals. This allows a reader to click on any element-noun in any section to display all related element-nouns and their reference numerals from the other sections.

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An apparatus to improve the readability of patent claims by structurally organizing the claim elements. It grabs the nouns, relationships, and objects from a claim. Then it reorganizes them using rules to determine noun order, separating and gathering, subordination, and matching relationships. The organized claim elements are displayed in a reader-friendly format.

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Modifying data structures representing patent claims such that the modified data structures include language elements in prose rather than patentese, providing a data structure with ordered content derived from patent claims, identifying and naming software components described by functional patent claim language, and using machine learning and rules-based algorithms to create a patent specification based on human-provided patent claims such that the patent specification is created without human intervention.

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A system for analyzing patent claims and retrieving relevant technology content to assist in patent examination and drafting. The system automatically imports patent claims, parses them hierarchically and generates a diagram that can be expanded or compressed. Users can click on diagram elements to search for matching technology content and display thumbnails linked to relevant claim elements.

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A computer-mediated patent application preparation system that uses a disclosure application to organize and generate patent application text. The system allows inventors to create a visual representation of their invention using disclosure views and limitation views. The arrangement of these views generates text for the patent application, such as the detailed description and claims. The system compares tangentially related data to the invention by analyzing the visual representation and generating text based on similarities and differences. This helps inventors identify potentially infringing prior art and assess the novelty of their invention.

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