The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 07, 2025

Filed:

Apr. 25, 2024
Applicant:

Goldman Sachs & Co. Llc, New York, NY (US);

Inventors:

Konstantin Kuchenmeister, New York, NY (US);

Alysa V Shcherbakova, Jersey City, NJ (US);

Demetrius Rowland, Dallas, TX (US);

Bing Xiang, Mount Kisco, NY (US);

Assignee:

Goldman Sachs & Co. LLC, New York, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/2457 (2019.01); G06F 16/22 (2019.01);
U.S. Cl.
CPC ...
G06F 16/24578 (2019.01); G06F 16/2246 (2019.01);
Abstract

The described system provides a dual-model framework for data retrieval from complex data environments such as webpages on the internet. It combines a traditional similarity model that identifies relevant data from vast amounts of data and a large language model that delves deeper into the relevant data to uncover specifics. The models, in conjunction, provide a method for providing responses to structured queries about an entity. A source investigator receives a request for information about an entity alongside a set of keywords. A source datastore is identified for the entity and a similarity model is applied to the datastore to determine relevancy scores for data within. Data and/or nodes above a relevancy threshold are stored as relevant data. Then, using the large language model, the investigator generates responses to the structured queries based on the relevant data and provides responses to the user system.


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