Granted Patent B2

US 12,626,060 · App. 18/452,085 · Granted May 12, 2026

Inventors: JoAnna Jean Butler (Huntsville, AL); Casey Hatcher Cooper (Hartselle, AL); Jaden Kadesh Flint (Harvest, AL); Jason LeVoy Rogers (Meridianville, AL); Keith Boyd Zook (New Market, AL); Kyle Jordan Russell (Huntsville, AL)

Assignee: Intuitive Research and Technology Corporation

G06F40/20

Abstract

Claims (44)

1 . A system for facilitating text analysis, comprising:

one or more processors; and

one or more hardware storage devices that store instructions that are executable by the one or more processors to configure the system to:

process input text data utilizing a syntax and verb usage module of a natural language processing (NLP) layer, wherein the input text data comprises a set of reference text and at least a first set of text, wherein the set of reference text and the first set of text each comprise structured components;

utilize output of the syntax and verb usage module as input to a categorization module of the NLP layer, wherein the categorization module is configured to map structured components of the first set of text to structured components of the set of reference text by generating embeddings based on the output of the syntax and verb usage module and categorizing the output of the syntax and verb usage module relative to predefined groupings determined via the categorization module based on the set of reference text;

utilize the output of the syntax and verb usage module as input to a similarity analysis module of the NLP layer, wherein the similarity analysis module is configured to map structured components of the first set of text to structured components of the set of reference text by comparing, in an embedding space, (i) embeddings generated via the similarity analysis module based on the output of the syntax and verb usage module and (ii) embeddings generated via the similarity analysis module based on the set of reference text;

fuse output of the categorization module and the similarity analysis module to generate a mapping of structured components of the first set of text to structured components of the set of reference text;

generate and present, on a user interface, (i) an output depicting one or more aspects of the mapping and (ii) a prompt, wherein the output depicts, for at least one structured component of the set of reference text, an indication of one or more structured components of the first set of text that are mapped to the at least one structured component, and wherein the prompt is associated in the user interface with the indication of the one or more structured components of the first set of text;

receive user input directed to the prompt, wherein the user input indicates rejection of the mapping of the one or more structured components of the first set of text to the at least one structured component of the set of reference text; and

tune one or more modules of the NLP layer based on the user input.

2 . The system of claim 1 , wherein the structured components of the set of reference text and the first set of text comprise sentences.

3 . The system of claim 1 , wherein the set of reference text comprises one or more reference documents, and wherein the first set of text comprises one or more first documents.

4 . The system of claim 3 , wherein the structured components of the set of reference text indicate one or more requirements, and wherein the mapping comprises a mapping of structured components of the one or more first documents to the one or more requirements of the set of reference text.

5 . The system of claim 1 , wherein the input text data comprises output of one or more preprocessing modules.

6 . The system of claim 1 , wherein the output of the syntax and verb usage module is further processed by a topic analysis module prior to generating the mapping.

7 . The system of claim 1 , wherein the indication of the one or more structured components indicates a quantity or a confidence level associated with the one or more structured components.

8 . The system of claim 7 , wherein the confidence level comprises a normalized confidence score.

9 . The system of claim 1 , wherein the indication of the one or more structured components indicates text content or a location associated with the one or more structured components.

10 . The system of claim 1 , wherein the input text data further comprises a second set of text that comprises structured components, and wherein the instructions are executable by the one or more processors to further configure the system to:

generate a second mapping of structured components of the second set of text to structured components of the set of reference text by processing output of the syntax and verb usage module utilizing the similarity analysis module or the categorization module of the NLP layer.

11 . The system of claim 10 , wherein the output depicting one or more aspects of the mapping further depicts one or more aspects of the second mapping.

12 . A method for facilitating text analysis, comprising:

processing input text data utilizing a syntax and verb usage module of a natural language processing (NLP) layer, wherein the input text data comprises a set of reference text and at least a first set of text, wherein the set of reference text and the first set of text each comprise structured components;

utilizing output of the syntax and verb usage module as input to a categorization module of the NLP layer, wherein the categorization module is configured to map structured components of the first set of text to structured components of the set of reference text by generating embeddings based on the output of the syntax and verb usage module and categorizing the output of the syntax and verb usage module relative to predefined groupings determined via the categorization module based on the set of reference text;

utilizing the output of the syntax and verb usage module as input to a similarity analysis module of the NLP layer, wherein the similarity analysis module is configured to map structured components of the first set of text to structured components of the set of reference text by comparing, in an embedding space, (i) embeddings generated via the similarity analysis module based on the output of the syntax and verb usage module and (ii) embeddings generated via the similarity analysis module based on the set of reference text;

fusing output of the categorization module and the similarity analysis module to generate a mapping of structured components of the first set of text to structured components of the set of reference text;

generating and presenting, on a user interface, (i) an output depicting one or more aspects of the mapping and (ii) a prompt, wherein the output depicts, for at least one structured component of the set of reference text, an indication of one or more structured components of the first set of text that are mapped to the at least one structured component, and wherein the prompt is associated in the user interface with the indication of the one or more structured components of the first set of text;

receiving user input directed to the prompt, wherein the user input indicates rejection of the mapping of the one or more structured components of the first set of text to the at least one structured component of the set of reference text; and

tuning one or more modules of the NLP layer based on the user input.

13 . The method of claim 12 , wherein the structured components of the set of reference text and the first set of text comprise sentences.

14 . The method of claim 12 , wherein the set of reference text comprises one or more reference documents, and wherein the first set of text comprises one or more first documents.

15 . The method of claim 14 , wherein the structured components of the set of reference text indicate one or more requirements, and wherein the mapping comprises a mapping of structured components of the one or more first documents to the one or more requirements of the set of reference text.

16 . The method of claim 12 , wherein the input text data comprises output of one or more preprocessing modules.

17 . The method of claim 12 , wherein the output of the syntax and verb usage module is further processed by a topic analysis module prior to generating the mapping.

18 . The method of claim 12 , wherein the indication of the one or more structured components indicates a quantity or a confidence level associated with the one or more structured components.

19 . The method of claim 12 , wherein the indication of the one or more structured components indicates text content or a location associated with the one or more structured components.

20 . One or more hardware storage devices that store instructions that are executable by one or more processors of a system to configure the system to:

process input text data utilizing a syntax and verb usage module of a natural language processing (NLP) layer, wherein the input text data comprises a set of reference text and at least a first set of text, wherein the set of reference text and the first set of text each comprise structured components;

utilize output of the syntax and verb usage module as input to a categorization module of the NLP layer, wherein the categorization module is configured to map structured components of the first set of text to structured components of the set of reference text by generating embeddings based on the output of the syntax and verb usage module and categorizing the output of the syntax and verb usage module relative to predefined groupings determined via the categorization module based on the set of reference text;

utilize the output of the syntax and verb usage module as input to a similarity analysis module of the NLP layer, wherein the similarity analysis module is configured to map structured components of the first set of text to structured components of the set of reference text by comparing, in an embedding space, (i) embeddings generated via the similarity analysis module based on the output of the syntax and verb usage module and (ii) embeddings generated via the similarity analysis module based on the set of reference text;

fuse output of the categorization module and the similarity analysis module to generate a mapping of structured components of the first set of text to structured components of the set of reference text;

generate and present, on a user interface, (i) an output depicting one or more aspects of the mapping and (ii) a prompt, wherein the output depicts, for at least one structured component of the set of reference text, an indication of one or more structured components of the first set of text that are mapped to the at least one structured component, and wherein the prompt is associated in the user interface with the indication of the one or more structured components of the first set of text;

receive user input directed to the prompt, wherein the user input indicates rejection of the mapping of the one or more structured components of the first set of text to the at least one structured component of the set of reference text; and

tune one or more modules of the NLP layer based on the user input.

Assignments (2)

Continuity (2)

References Cited (14)