-
公开(公告)号:US20230419050A1
公开(公告)日:2023-12-28
申请号:US18463019
申请日:2023-09-07
Applicant: salesforce.com, inc.
Inventor: Akari ASAI , Kazuma HASHIMOTO , Richard SOCHER , Caiming XIONG
IPC: G06F40/40
Abstract: Embodiments described herein provide a pipelined natural language question answering system that improves a BERT-based system. Specifically, the natural language question answering system uses a pipeline of neural networks each trained to perform a particular task. The context selection network identifies premium context from context for the question. The question type network identifies the natural language question as a yes, no, or span question and a yes or no answer to the natural language question when the question is a yes or no question. The span extraction model determines an answer span to the natural language question when the question is a span question.
-
公开(公告)号:US20200372341A1
公开(公告)日:2020-11-26
申请号:US16695494
申请日:2019-11-26
Applicant: salesforce.com, inc.
Inventor: Akari ASAI , Kazuma HASHIMOTO , Richard SOCHER , Caiming XIONG
Abstract: Embodiments described herein provide a pipelined natural language question answering system that improves a BERT-based system. Specifically, the natural language question answering system uses a pipeline of neural networks each trained to perform a particular task. The context selection network identifies premium context from context for the question. The question type network identifies the natural language question as a yes, no, or span question and a yes or no answer to the natural language question when the question is a yes or no question. The span extraction model determines an answer span to the natural language question when the question is a span question.
-