The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 17, 2025

Filed:

Jul. 12, 2022
Applicant:

Beijing Baidu Netcom Science Technology Co., Ltd., Beijing, CN;

Inventors:

Wenbin Jiang, Beijing, CN;

Yajuan Lyu, Beijing, CN;

Yong Zhu, Beijing, CN;

Hua Wu, Beijing, CN;

Haifeng Wang, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/24 (2019.01); G06F 16/21 (2019.01); G06F 16/242 (2019.01); G06F 16/245 (2019.01); G06N 5/02 (2023.01);
U.S. Cl.
CPC ...
G06F 16/243 (2019.01); G06F 16/212 (2019.01); G06F 16/245 (2019.01); G06N 5/02 (2013.01);
Abstract

The present disclosure discloses a method for acquiring a structured question-answering (QA) model, a QA method and corresponding apparatuses, and relates to knowledge graph and deep learning technologies in the field of artificial intelligence technologies. A specific implementation solution involves: acquiring training samples corresponding to N structured QA database types, the training samples including question samples, information of the structured QA database types and query instruction samples used by the question samples to query structured QA databases of the types, N being an integer greater than 1; and training a text generation model by using the training samples to obtain the structured QA model, wherein the question samples and the information of the structured QA database types are taken as input to the text generation model, and the query instruction samples are taken as target output of the text generation model.


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