Title:
TRAINING METHOD AND APPARATUS FOR NAMED ENTITY MODEL, DEVICE, AND MEDIUM
Document Type and Number:
WIPO Patent Application WO/2022/142123
Kind Code:
A1
Abstract:
The present application relates to the technical field of artificial intelligence, and discloses a training method and apparatus for a named entity model, a device, and a medium. The method comprises: acquiring a plurality of incompletely labeled training samples, the incompletely labeled training samples comprising: text sample data and an incompletely labeled label sequence; determining an estimated label sequence of each incompletely labeled training sample by means of preset estimation rules, and obtaining an estimated label sequence set respectively corresponding to the plurality of incompletely labeled training samples; and acquiring a named entity model for preliminary training, and using an adaptive loss function, the named entity model for preliminary training, the plurality of incompletely labeled training samples and the estimated label sequence set respectively corresponding to the plurality of incompletely labeled training samples to train a named entity model to be trained so as to obtain a target named entity model. Hence, dependence on labeling quality is reduced, and an adaptive loss function is used to avoid redirecting attention towards a large number of label sequences during training.
Inventors:
RUAN HONGTAO (CN)
ZHENG LIYING (CN)
HU PEIXIAN (CN)
XU LIANG (CN)
ZHENG LIYING (CN)
HU PEIXIAN (CN)
XU LIANG (CN)
Application Number:
PCT/CN2021/097545
Publication Date:
July 07, 2022
Filing Date:
May 31, 2021
Export Citation:
Assignee:
PING AN TECH SHENZHEN CO LTD (CN)
International Classes:
G06N3/08
Foreign References:
| CN112766485A | 2021-05-07 | |||
| CN111382572A | 2020-07-07 | |||
| CN110287480A | 2019-09-27 | |||
| CN110032649A | 2019-07-19 | |||
| US20200050662A1 | 2020-02-13 |
Attorney, Agent or Firm:
SHENZHEN MINGRIJINDIAN INTELLECTUAL PROPERTY AGENCY FIRM(GENERAL) (CN)
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