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公开(公告)号:US12182724B2
公开(公告)日:2024-12-31
申请号:US17025952
申请日:2020-09-18
Inventor: Fang Huang , Shuangjie Li , Yabing Shi , Ye Jiang , Yang Zhang , Yong Zhu
Abstract: A method and apparatus for generating a temporal knowledge graph, a device and a medium. An embodiment comprises: acquiring corpus including time information; performing multivariate data extraction on the corpus, multivariate data including an entity pair, an entity relationship and a target time interval of the entity relationship, the target time interval being used to indicate a valid period of the entity relationship; and generating a temporal knowledge graph based on the entity pair, the entity relationship and the target time interval of the entity relationship.
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公开(公告)号:US11775776B2
公开(公告)日:2023-10-03
申请号:US17147881
申请日:2021-01-13
Inventor: Shuangjie Li , Miao Yu , Yabing Shi , Xuefeng Hao , Xunchao Song , Ye Jiang , Yang Zhang , Yong Zhu
IPC: G06F40/40 , G06N20/00 , G06F40/289
CPC classification number: G06F40/40 , G06F40/289 , G06N20/00
Abstract: A method and an apparatus for processing information are provided. The method can include: acquiring a word sequence obtained by performing word segmentation on two paragraphs in a text; inputting the word sequence into a to-be-trained natural language processing model to generate a word vector corresponding to a word in the word sequence; inputting the word vector into a preset processing layer of the to-be-trained natural language processing model; predicting whether the two paragraphs are adjacent, and a replaced word in the two paragraphs; and acquiring reference information of the two paragraphs, and training the to-be-trained natural language processing model to obtain a trained natural language processing model, based on the prediction result and the reference information.
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公开(公告)号:US11636936B2
公开(公告)日:2023-04-25
申请号:US17023998
申请日:2020-09-17
Inventor: Zhou Fang , Shuangjie Li , Yabing Shi , Ye Jiang
Abstract: The present disclosure relates to the field of medical data processing based on natural language processing. Embodiments of the present disclosure disclose a method and apparatus for verifying a medical fact. The method may include: acquiring a description text of the medical fact; selecting a relevant paragraph related to the description text of the medical fact from a medical document; and inputting the description text of the medical fact and the corresponding relevant paragraph into a trained discrimination model for authenticity judgment, to obtain a verification result of the medical fact, the discrimination model being pre-trained based on a medical text paragraph pair extracted from the medical document, and being iteratively adjusted using a medical fact sample set including authenticity labeling information after the pre-training.
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公开(公告)号:US11361002B2
公开(公告)日:2022-06-14
申请号:US17249001
申请日:2021-02-17
Inventor: Yabing Shi , Shuangjie Li , Ye Jiang , Yang Zhang , Yong Zhu
IPC: G06F16/28 , G06F40/295 , G06F40/30 , G06N20/00
Abstract: The disclosure discloses a method and an apparatus for recognizing an entity word. The method includes: obtaining an entity word category and a document to be recognized; generating an entity word question based on the entity word category; segmenting the document to be recognized to generate a plurality of candidate sentences; inputting the entity word question and the plurality of candidate sentences into a question-answer model trained in advance to obtain an entity word recognizing result; and obtaining an entity word set corresponding to the entity word question based on the entity word recognizing result.
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公开(公告)号:US20210374576A1
公开(公告)日:2021-12-02
申请号:US17132704
申请日:2020-12-23
Inventor: Zhou Fang , Yabing Shi , Ye Jiang , Chunguang Chai
Abstract: A medical fact verification method and apparatus, an electronic device, and a storage medium are provided. The medical fact verification method comprises: acquiring a medical fact to be verified and candidate evidence, wherein the medical fact to be verified includes a target entity, a target attribute and a target attribute value; inputting the target entity, the target attribute value and the candidate evidence into an attribute decision model to obtain a decision attribute; inputting the target entity, the target attribute value and the candidate evidence into a relevancy decision model to obtain a relevancy of the candidate evidence in a case that the target attribute and the decision attribute are the same; and determining that the medical fact to be verified is correct in a case that the relevancy of the candidate evidence accords with a preset condition.
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