公开(公告)号：US20220229987A1

公开(公告)日：2022-07-21

申请号：US17579233

申请日：2022-01-19

Applicant: ServiceNow, Inc.

Inventor： Sagar Davasam Suryanarayan ,  Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Vipulkumar Popat Mahadik ,  Edward Cheung

IPC: G06F40/284 ,  G06F40/253 ,  G06F40/30 ,  G06F40/166 ,  G06N20/00

Abstract: A natural language understanding (NLU) framework includes a lookup source framework, which enables a lookup source system to be defined having one or more lookup sources. The lookup source system can operate in a number of different manners to facilitate repository-aware inference of user utterances, for example, by facilitating vocabulary injection during compilation of an utterance meaning model and/or an understanding model. Additionally, the lookup source system can be leveraged to cleanse client-specific training data of sensitive values to generate generic training data that can be used to train the NLU framework of other clients. The lookup sources can be compiled in a synchronous or asynchronous manner, which enables lookup sources to be compiled in an on-demand basis from test source data. Additionally, understanding models that reference lookup sources can be periodically recompiled while leveraging the latest versions of the lookup sources for vocabulary injection.

公开(公告)号：US12299391B2

公开(公告)日：2025-05-13

申请号：US17579233

申请日：2022-01-19

Applicant: ServiceNow, Inc.

Inventor： Sagar Davasam Suryanarayan ,  Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Vipulkumar Popat Mahadik ,  Edward Cheung

IPC: G06F40/284 ,  G06F40/166 ,  G06F40/253 ,  G06F40/30 ,  G06N20/00

Abstract: A natural language understanding (NLU) framework includes a lookup source framework, which enables a lookup source system to be defined having one or more lookup sources. The lookup source system can operate in a number of different manners to facilitate repository-aware inference of user utterances, for example, by facilitating vocabulary injection during compilation of an utterance meaning model and/or an understanding model. Additionally, the lookup source system can be leveraged to cleanse client-specific training data of sensitive values to generate generic training data that can be used to train the NLU framework of other clients. The lookup sources can be compiled in a synchronous or asynchronous manner, which enables lookup sources to be compiled in an on-demand basis from test source data. Additionally, understanding models that reference lookup sources can be periodically recompiled while leveraging the latest versions of the lookup sources for vocabulary injection.