US 12,032,918 B1
Agent based methods for discovering and documenting user expectations
Dustin Garvey, Exeter, NH (US); Charlie Hoang, Boston, MA (US); Alexa Stewart, Andover, MA (US); Janet Muto, Boston, MA (US); Nitzan Shaer, Boston, MA (US); Andrea Paola Aguilera García, Cambridge, MA (US); Jon Andrews, Boston, MA (US); and Frank Chiang, Boston, MA (US)
Assigned to Wevo, Inc., Boston, MA (US)
Filed by Wevo, Inc., Boston, MA (US)
Filed on Aug. 31, 2023, as Appl. No. 18/240,627.
Int. Cl. G06F 40/40 (2020.01)
CPC G06F 40/40 (2020.01) 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving data that includes a plurality of unstructured textual elements;
generating, by a machine learning classification model, a set of theme assignments for at least a subset of the unstructured textual elements, wherein the set of theme assignments map each unstructured textual element of the subset to one or more themes from a theme schema;
sending the set of theme assignments to a generative language model for review;
updating at least one theme assignment made by the machine learning classification model based at least in part on an output of the generative language model; and
sending a second prompt to at least one of the generative language model or a second generative language model to select representative quotes for at least a first outcome and second outcome associated with a first theme, wherein the second prompt is generated based at least in part on the output of the generative language model.