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.

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.

Abstract: A method is provided that includes: obtaining a text; inputting the text and a first question into a first machine reading comprehension model to obtain a first round of answer, wherein the first question inquires about cause of a causal relationship in the text, and the first round of answer includes at least one cause; and inputting the text and a second question into a second machine reading comprehension model to obtain a second round of answer, wherein the second question inquires about effect of the causal relationship in the text, and the second round of answer includes at least one effect of the at least one cause.

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.

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.

Abstract: The present disclosure provides a method for generating an event theme, belonging to a field of knowledge graph technologies and a field of deep learning technologies. Pieces of event information in an associated relation are obtained. Entity information and an event type of each piece of event information are obtained. Target event information having representative attributes is obtained from the pieces of event information. A theme template matching the event type of the target event information is selected from a theme template collection. The entity information and the event type of the target event information are added into the theme template to generate a theme of the pieces of event information.

Abstract: An event argument extraction method, an event argument extraction apparatus and an electronic device are disclosed, which relate to the field of artificial intelligence. A specific implementation is: acquiring to-be-extracted event content; and performing an argument extraction on the to-be-extracted event content based on a trained event argument extraction model, to acquire an target argument of the to-be-extracted event content; where, the trained event argument extraction model is acquired by training an intermediate extraction model by using event news annotation data, and the intermediate extraction model is acquired by training a pre-trained model by using event news samples and reading comprehension data.

Abstract: The present invention discloses a frame assembly of movable stowage device and its application as a transport vehicle. The frame assembly moving stowage comprises a frame, a rolling chute, a drive sprocket, a driven sprocket, a transmission chain, a towing hook device, a towing hook guide-rail and a power device. The frame assembly can be used to load and unload a dustbin with a transfer vehicle. No special lifting equipment is required when the frame assembly is used. The automatic and modern transport vehicle of present invention makes the transportation of garbage faster and more efficient, which meets the desired requirements of logistics for the transportation of garbage.

Abstract: The present invention discloses a frame assembly of movable stowage device and its application as a transport vehicle. The frame assembly moving stowage comprises a frame, a rolling chute, a drive sprocket, a driven sprocket, a transmission chain, a towing hook device, a towing hook guide-rail and a power device. The frame assembly can be used to load and unload a dustbin with a transfer vehicle. No special lifting equipment is required when the frame assembly is used. The automatic and modern transport vehicle of present invention makes the transportation of garbage faster and more efficient, which meets the desired requirements of logistics for the transportation of garbage.