Patent ID: 11886820
Assignee: GENPACT LUXEMBOURG S.à R.L. II
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. A system for providing a machine-learning (ML) model, the system comprising:
a processor; and
a memory in communication with the processor and comprising instructions which, when executed by the processor, program the processor to:
(a) provide a seed set of labeled entities as a labeled entities set based on a first cluster of a plurality of clusters of documents and use the labeled entities set to train a machine learning (ML) module, to obtain the ML model;
(b) use the trained ML module to predict labels for entities in an unlabeled entities set, yielding a machine-labeled entities set, the prediction providing a respective confidence score for each machine-labeled entity;
(c) select from the machine-labeled entities set, a subset of machine-labeled entities having a respective confidence score at least equal to a threshold confidence score;
(d) update the labeled entities set by adding thereto the selected subset of machine-labeled entities;
(e) remove from the machine-labeled entities set the selected subset of machine-labeled entities and delete labels assigned to the entities in the updated machine-labeled entities set to provide the unlabeled entities set for a next iteration;
(f) if a termination condition is not reached, repeat operations (a) through (e) and, otherwise, store the ML model;
(g) select a second cluster from the plurality of clusters; and

(h) repeat the steps (a) through (f) for the second cluster to store a different ML model for the second cluster, wherein providing the seed set in step (a) is based on the second cluster.