Multi-dimensional entity generation from natural language input
The system addresses the inefficiency in generating multidimensional entities by using natural language input and prompt templates to create outputs relevant to computer-aided design and 3D manufacturing, enhancing the generation of MDEs for these applications and file formats.
Patent Information
- Authority / Receiving Office
- HK · HK
- Patent Type
- Applications
- Current Assignee / Owner
- MICROSOFT TECHNOLOGY LICENSING LLC
- Filing Date
- 2026-04-20
- Publication Date
- 2026-07-10
AI Technical Summary
Existing systems lack the ability to efficiently generate multidimensional entities (MDEs) based on natural language input, particularly in applications like computer-aided design and 3D manufacturing, where the generation of outputs associated with specific file formats is not effectively supported.
A system and method for creating MDEs using natural language input, where skills are identified and associated with prompt templates, enabling the generation of outputs relevant to computer-aided design and 3D manufacturing applications and file formats, and allowing for the creation of skill chains for generating corresponding outputs.
Enables the efficient generation of multidimensional entities from natural language input, supporting applications in computer-aided design and 3D manufacturing by generating outputs relevant to these domains and file formats.
Smart Images
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Abstract
Description
HK Application no : <S1_APPLICATION_NO> Our Ref : SHPA26 / 11333 <deadline> <iinitial><letter_date>Abstract: This publicly disclosed aspect of multidimensional entity generation based on natural language input relates to systems and methods for creating multidimensional entities (MDEs) based on natural language (NL) input. Users can provide NL input to applications. One or more skills can be identified for the NL input, each with an associated prompt template. For example, skills may be associated with computer-aided design and / or 3D manufacturing applications and / or file formats, thereby allowing the generation of outputs associated with such applications and / or file formats. In various examples, skill chains can be generated, including one or more skills for correspondingly generating MDE outputs.< / iinitial> < / deadline>
Claims
CLAIMS1. A system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising: receiving, from a computing device, a natural language input that includes a description of a multi-dimensional entity; generating, using a machine learning model, multi-dimensional entity output responsive to the natural language input, wherein the multi-dimensional entity output defines a representation of the multi-dimensional entity; and providing, to the computing device the generated multi-dimensional entity output.
2. The system of claim 1 , wherein generating the model output comprises: generating, based on the natural language input, a skill chain to generate the indicated multi-dimensional entity, wherein each skill of the skill chain is associated with at least a portion of the user input; for each skill in the skill chain: populating a prompt template corresponding to each skill; and processing, using a machine learning model, the prompt template for each skill to generate model output for the skill; and combining the model output for each skill of the skill chain to generate multi-dimensional entity output that is responsive to the natural language input.
3. The system of claim 2, wherein the natural language input includes a target output indication of at least one of a target application or a target data format for the multi-dimensional entity output.
4. The system of claim 3, wherein a skill of the skill chain is associated with the target output indication, thereby generating the multi-dimensional entity output according to the target output indication.
5. The system of claim 2, wherein: a first skill of the skill chain is associated with a first subpart of the multi-dimensional entity; and a second skill of the skill chain is associated with a second subpart of the multidimensional entity.
6. The system of claim 5, wherein a third skill of the skill chain processes model output of the first skill and model output of the second skill to generate the multi-dimensional entity output.
7. The system of claim 1 , wherein the generated multi-dimensional entity output includes at least one of: instructions to render the multi-dimensional entity in a virtual environment; or instructions to fabricate a physical representation of the multi-dimensional entity.
8. A method, comprising obtaining user input corresponding to a multi-dimensional entity, wherein the user input includes a target output indication; generating a request to generate multi-dimensional entity output using a machine learning model, wherein the request includes the target output indication; receiving, in response to the request, the multi-dimensional entity output; and generating, based on the multi-dimensional entity output, a display of the multidimensional entity.
9. The method of claim 8, wherein: the user input corresponding to the multi-dimensional entity comprises an indication of the multi-dimensional entity in a first format; and the target output indication corresponds to a second format that is different than the first format.
10. The method of claim 9, wherein the request further comprises a representation of the multi-dimensional entity in the first format.
11. The method of claim 8, wherein the target output indication indicates at least one of a target application or a target data format for the multi-dimensional entity output.
12. The method of claim 8, wherein: the method further comprises processing the user input to generate a skill chain comprising one or more skills; and the request to generate the multi-dimensional entity comprises a request to process a skill of the generated skill chain.
13. The method of claim 12, wherein a skill of the skill chain is associated with the target output indication, thereby generating the multi-dimensional entity output according to the target output indication.
14. A method, comprising: receiving, from a computing device, a natural language input that includes an indication of a multi-dimensional entity; generating, based on the natural language input, a skill chain to generate the indicated multi-dimensional entity, wherein each skill of the skill chain is associated with at least a portion of the user input;for each skill in the skill chain: populating a prompt template corresponding to each skill; processing, using a machine learning model, the prompt template for each skill to generate model output for the skill; combining the model output for each skill of the skill chain to generate multidimensional entity output that is responsive to the natural language input; and providing, to the computing device the generated multi-dimensional entity output.
15. The method of claim 14, wherein the natural language input includes a target output indication of at least one of a target application or a target data format for the multi-dimensional entity output.