Abstract: A computing system includes a processor and memory storing instructions that, when executed by the processor, cause the processor to perform acts. The acts include receiving a query provided by a user. The acts additionally include determining that the query is related to a comparison between entities. Based upon the determining that the query is related to the comparison between entities, the computing system generates a prompt that is to be input to a generative language model, where the prompt includes: 1) an instruction for the generative language model to generate a table based upon the query; and 2) attribute values for entities identified by a search system based upon the query. The acts also include providing the prompt as input to the generative language model, where the generative language model generates a table based upon the prompt, and further where the table includes the attribute values for the entities.

Abstract: Aspects of the present disclosure relate to providing a shoppable video corpus by generating a shoppable URL. A URL is extracted from a video corpus, in which the extracted URL may be a long URL or a short URL. Extracted URLs are then combined and normalized. From the normalized URL, noise is removed and quality control is performed. As a result, shoppable URL may be presented at the user's computing device as personal recommendation. The video and metadata of the cleaned URL is also ingested and stored in a database for future reference.

Abstract: A computing system includes a processor and memory storing instructions that, when executed by the processor, cause the processor to perform acts. The acts include receiving a query provided by a user. The acts additionally include determining that the query is related to a comparison between entities. Based upon the determining that the query is related to the comparison between entities, the computing system generates a prompt that is to be input to a generative language model, where the prompt includes: 1) an instruction for the generative language model to generate a table based upon the query; and 2) attribute values for entities identified by a search system based upon the query. The acts also include providing the prompt as input to the generative language model, where the generative language model generates a table based upon the prompt, and further where the table includes the attribute values for the entities.