Abstract: In various examples there is a knowledge base construction and/or maintenance system for use with a probabilistic knowledge base. The system has a probabilistic generative model comprising a process for generating text or other formatted data from the knowledge base. The system has an inference component configured to generate inference results, by carrying out inference using inference algorithms, run on the probabilistic generative model, in either a forward direction whereby text or other formatted data is generated, or a reverse direction whereby text or other formatted data is observed and at least one unobserved variable of the probabilistic generative model is inferred. The inference component is configured to update the knowledge base using at least some of the inference results.

Abstract: Technology is disclosed herein for an application service which interfaces with an LLM service. In an implementation, the application service receives a natural language input from a user associated with a spreadsheet. The application service generates multiple prompts based on the natural language input and a portion of the spreadsheet and determines an order in which to input the prompts to an LLM service. The application service determines an order in which to input the prompts to an LLM service, then inputs the prompts to the LLM service according to the determined order.

Abstract: Technology is disclosed herein for an application service which interfaces with an LLM service. In an implementation, the application service receives a natural language input from a user associated with a spreadsheet. The application service generates a prompt based on the user input and at least a portion of the spreadsheet. The prompt constrains the LLM service to a domain specific to the spreadsheet based on the portion and submits the prompt to the LLM service. The application service receives a reply to the prompt from the LLM service and responds to the input based on the reply from the LLM service.

Abstract: Technology is disclosed herein for the integration of spreadsheet environments and LLM services. In an implementation, an application receives a natural language input from a user associated with a spreadsheet. The application generates a prompt based on the user input and at least a portion of the spreadsheet. The prompt includes a statement of the problem, a request for an LLM service to identify preparatory steps before generating a solution to the problem, and a request to include the preparatory steps in output that includes the solution to problem. The application service receives a reply to the prompt from the LLM service that includes the output. The application service implements the preparatory steps with respect to data in the spreadsheet and implements the solution to the problem with respect to the data in the spreadsheet.

Abstract: Technology is disclosed herein for the integration of spreadsheet environments and LLM services. In an implementation, an application service inputs a first prompt to a LLM service to provide a formula suggestion for a spreadsheet. The application service receives a first output from the LLM service that includes a first formula in a programming language having a syntax that does not support comments. The application service generates a second prompt instructing the LLM service to provide a chain-of-thought breakdown of the first formula and receives a second output. The second output includes a second formula in the same programming language as the first formula and multiple comments corresponding to multiple portions of the second formula.

Abstract: Technology is disclosed herein for the integration of spreadsheet environments and LLM services. In an implementation, an application service inputs a first prompt to a LLM service to provide a formula suggestion for a spreadsheet. The application service receives a first output from the LLM service that includes a first formula in a programming language having a syntax that does not support comments. The application service generates a second prompt instructing the LLM service to provide a chain-of-thought breakdown of the first formula and receives a second output. The second output includes a second formula in the same programming language as the first formula and multiple comments corresponding to multiple portions of the second formula.

Abstract: Technology is disclosed herein for an application service which interfaces with an LLM service. In an implementation, the application service receives a natural language input from a user associated with a spreadsheet. The application service generates multiple prompts based on the natural language input and a portion of the spreadsheet and determines an order in which to input the prompts to an LLM service. The application service determines an order in which to input the prompts to an LLM service, then inputs the prompts to the LLM service according to the determined order.

Abstract: Technology is disclosed herein for the integration of spreadsheet environments and LLM services. In an implementation, an application receives a natural language input from a user associated with a spreadsheet. The application generates a prompt based on the user input and at least a portion of the spreadsheet. The prompt includes a statement of the problem, a request for an LLM service to identify preparatory steps before generating a solution to the problem, and a request to include the preparatory steps in output that includes the solution to problem. The application service receives a reply to the prompt from the LLM service that includes the output. The application service implements the preparatory steps with respect to data in the spreadsheet and implements the solution to the problem with respect to the data in the spreadsheet.

Abstract: Technology is disclosed herein for an application service which interfaces with an LLM service. In an implementation, the application service receives a natural language input from a user associated with a spreadsheet. The application service generates a prompt based on the user input and at least a portion of the spreadsheet. The prompt constrains the LLM service to a domain specific to the spreadsheet based on the portion. and submits the prompt to the LLM service. The application service receives a reply to the prompt from the LLM service and responds to the input based on the reply from the LLM service.

Abstract: Technology is disclosed herein for an application service which interfaces with an LLM service. In an implementation, the application service receives a natural language input from a user associated with a spreadsheet. The application service generates a prompt based on the user input and at least a portion of the spreadsheet and submits the prompt to a large language model (LLM) service. The application service receives a reply to the prompt from the LLM service and responds to the input based on the reply from the LLM service.

Abstract: In various examples there is a knowledge base construction and/or maintenance system for use with a probabilistic knowledge base. The system has a probabilistic generative model comprising a process for generating text or other formatted data from the knowledge base. The system has an inference component configured to generate inference results, by carrying out inference using inference algorithms, run on the probabilistic generative model, in either a forward direction whereby text or other formatted data is generated, or a reverse direction whereby text or other formatted data is observed and at least one unobserved variable of the probabilistic generative model is inferred. The inference component is configured to update the knowledge base using at least some of the inference results.