公开(公告)号：US20240143945A1

公开(公告)日：2024-05-02

申请号：US18161767

申请日：2023-01-30

Applicant: Salesforce, Inc.

Inventor： Shubham Mehrotra ,  Zachary Alexander ,  Shilpa Bhagavath ,  Gurkirat Singh ,  Shashank Harinath ,  Anuprit Kale

IPC: G06F40/47 ,  G06F40/30 ,  G06F40/51

CPC classification number: G06F40/47 ,  G06F40/30 ,  G06F40/51

Abstract: Embodiments described herein provide a cross-lingual intent classification model that predicts in multiple languages without the need of training data in all the multiple languages. For example, data requirement for training can be reduced to just one utterance per intent label. Specifically, when an utterance is fed to the intent classification model, the model checks whether the utterance is similar to any of the example utterances provided for each intent. If any such utterance(s) are found, the model returns the specified intent, otherwise, it returns out of domain (OOD).

公开(公告)号：US12001798B2

公开(公告)日：2024-06-04

申请号：US17202188

申请日：2021-03-15

Applicant: Salesforce, Inc.

Inventor： Jingyuan Liu ,  Abhishek Sharma ,  Suhail Sanjiv Barot ,  Gurkirat Singh ,  Mridul Gupta ,  Shiva Kumar Pentyala ,  Ankit Chadha

IPC: G06F40/295 ,  G06F18/214 ,  G06F40/247 ,  G06F40/284 ,  G06F40/35 ,  G06N3/08 ,  G06N20/00 ,  H04L51/02

CPC classification number: G06F40/295 ,  G06F18/214 ,  G06F40/247 ,  G06F40/284 ,  G06F40/35 ,  G06N3/08 ,  G06N20/00 ,  H04L51/02

Abstract: A system performs named entity recognition for performing natural language processing, for example, for conversation engines. The system uses context information in named entity recognition. The system includes the context of a sentence during model training and execution. The system generates high quality contextual data for training NER models. The system utilizes labeled and unlabeled contextual data for training NER models. The system provides NER models for execution in production environments. The system uses heuristics to determine whether to use a context-based NER model or a simple NER model that does not use context information. This allows the system to use simple NER models when the likelihood of improving the accuracy of prediction based on context is low.