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公开(公告)号：US20220004714A1
公开(公告)日：2022-01-06
申请号：US17479636
申请日：2021-09-20
Inventor： Xinyu Li , Fayuan Li , Lu Pan , Yuguang Chen
IPC: G06F40/289 , G06F40/35
Abstract: The present disclosure provides an event extraction method and apparatus, and a storage medium. The method includes: obtaining an event description text; determining at least one candidate event type according to the event description text, wherein the candidate event type corresponds to a set of query sentences; and extracting a corresponding event element from the event description text according to the query sentence.
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公开(公告)号：US11625539B2
公开(公告)日：2023-04-11
申请号：US17113748
申请日：2020-12-07
Inventor： Lu Pan , Yuguang Chen , Fayuan Li
IPC: G06F40/279 , G06F40/30 , G06N3/045 , G06F40/284 , G06F40/289
Abstract: A method for extracting an event from a text including obtaining an input text; inputting the input text into a model for extracting trigger words to obtain a trigger word extraction result of the input text; inputting the input text and the trigger word extraction result into a model for extracting arguments to obtain an argument extraction result of the input text; and obtaining an event extraction result of the input text according to the trigger word extraction result and the argument extraction result.
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公开(公告)号：US11928435B2
公开(公告)日：2024-03-12
申请号：US17034394
申请日：2020-09-28
Inventor： Lu Pan , Yuguang Chen , Fayuan Li , Cuiyun Han , Yuanzhen Liu , Jiayan Huang
IPC: G06F40/30 , G06F18/21 , G06F18/2113 , G06F18/213 , G06F18/25 , G06F40/284
CPC classification number: G06F40/30 , G06F18/2113 , G06F18/213 , G06F18/2163 , G06F18/253 , G06F40/284
Abstract: The present disclosure provides an event extraction method, an event extraction device and an electronic device, and it relates to the field of computer data processing, in particular to the field of knowledge graph. The event extraction method includes: acquiring text information; determining a plurality of pieces of question information ranked in a sequential order in accordance with the text information; and inputting vector information for each piece of question information into an extraction model in accordance with the sequential order to acquire extraction information for each piece of question information.
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公开(公告)号：US20210312308A1
公开(公告)日：2021-10-07
申请号：US17351146
申请日：2021-06-17
Inventor： Yuguang Chen , Xiaojin Zhou
Abstract: A computer-implemented method is provided. The method includes: acquiring, by one or more computers, a first input including a first text and a question set associated with the first text, wherein the first input includes a first separation identifier for separating a plurality of questions in the question set; determining, by one or more computers, a question index for indicating a position of the first separation identifier in the first input, and a question mask for the question set, wherein the question mask is configured to screen the question set in the first input; and based on the question index, the question mask and a reading comprehension model, determining, by one or more computers, a first output corresponding to the first input for generating a plurality of answers corresponding to the plurality of questions respectively.
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公开(公告)号：US20210209472A1
公开(公告)日：2021-07-08
申请号：US17211381
申请日：2021-03-24
Inventor： Yuguang Chen , Lu Pan , Yanhui Huang
Abstract: Embodiments of the present disclosure provide a method for determining causality, an apparatus for determining causality, an electronic device and a storage medium, and relates to a field of knowledge graph technologies. The method includes: obtaining event words expressing individual events and related words adjacent to the event words in a target text; inputting the event words and the related words into a graph neural network; and determining whether there is a causal relationship between any two events through the graph neural network.
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Patent Agency Ranking
公开(公告)号：US11573992B2
公开(公告)日：2023-02-07
申请号：US17105707
申请日：2020-11-27
Inventor： Shangru Zhong , Yuguang Chen , Weihua Peng
IPC: G06F16/33 , G06F16/332 , G06F40/279 , G06K9/62 , G06N3/08
Abstract: A method for generating a relationship of events includes: obtaining a statement of a first event and a statement of a second event; generating a word sequence vector with first granularity and a word sequence vector with second granularity based on the statement of the first event; generating a word sequence vector with third granularity and a word sequence vector with fourth granularity based on the statement of the second event; generating a first fusion vector based on the word sequence vector with first granularity and the word sequence vector with second granularity; generating a second fusion vector based on the word sequence vector with third granularity and the word sequence vector with fourth granularity; and determining a relationship between the first event and the second event based on the first fusion vector and the second fusion vector.
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公开(公告)号：US20210295095A1
公开(公告)日：2021-09-23
申请号：US17034394
申请日：2020-09-28
Inventor： Lu Pan , Yuguang Chen , Fayuan Li , Cuiyun Han , Yuanzhen Liu , Jiayan Huang
IPC: G06K9/62 , G06F40/284
Abstract: The present disclosure provides an event extraction method, an event extraction device and an electronic device, and it relates to the field of computer data processing, in particular to the field of knowledge graph. The event extraction method includes: acquiring text information; determining a plurality of pieces of question information ranked in a sequential order in accordance with the text information; and inputting vector information for each piece of question information into an extraction model in accordance with the sequential order to acquire extraction information for each piece of question information.
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8.发明授权公开(公告)号：US11880397B2
公开(公告)日：2024-01-23
申请号：US17036833
申请日：2020-09-29
Inventor： Fayuan Li , Yuguang Chen , Lu Pan , Yuanzhen Liu , Cuiyun Han , Xi Shi , Jiayan Huang
IPC: G06F18/214 , G06F16/33 , G06V20/20 , G06V20/40 , G06F18/2415
CPC classification number: G06F16/3344 , G06F18/214 , G06F18/2415 , G06V20/20 , G06V20/43
Abstract: An event argument extraction (EAE) method, an EAE apparatus and an electronic device, relates to the technical field of knowledge graphs. A specific implementation scheme includes acquiring a to-be-extracted event content; and performing argument extraction on the to-be-extracted event content based on a trained EAE model, to obtain a target argument of the to-be-extracted event content; where the trained EAE model is obtained by training a pre-trained model with event news annotation data and a weight of each argument annotated in the event news annotation data.
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公开(公告)号：US11494420B2
公开(公告)日：2022-11-08
申请号：US16355304
申请日：2019-03-15
Inventor： Yuguang Chen , Lu Pan , Wenhao Chen , Hui Zhou , Weina Chen , Yuhong Zheng
Abstract: A method and apparatus for generating information are disclosed. An implementation of the method includes: receiving a target text, the target text including an objective and descriptive information of the objective; performing a dependency syntax parsing on the target text to generate a dependency tree of the target text; matching predetermined syntactic structure tree with the dependency tree to obtain at least one triple, a triple including a subject, a predicate, and an object; and determining, based on words contained in a triple among the at least one triple and a predetermined weight of the syntactic structure tree matched to obtain the triple, a target triple among the at least one triple.
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10.发明申请公开(公告)号：US20210295098A1
公开(公告)日：2021-09-23
申请号：US17036833
申请日：2020-09-29
Inventor： Fayuan Li , Yuguang Chen , Lu Pan , Yuanzhen Liu , Cuiyun Han , Xi Shi , Jiayan Huang
Abstract: An event argument extraction (EAE) method, an EAE apparatus and an electronic device, relates to the technical field of knowledge graphs. A specific implementation scheme includes acquiring a to-be-extracted event content; and performing argument extraction on the to-be-extracted event content based on a trained EAE model, to obtain a target argument of the to-be-extracted event content; where the trained EAE model is obtained by training a pre-trained model with event news annotation data and a weight of each argument annotated in the event news annotation data.
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